PhishFinder_LinkPrediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook will form the evaluation on which model to select for my PhishGuard tool.\n",
    "Consider the data that is to be trained I am considering the following models:\n",
    "- K - Nearest Neighbours (KNN)\n",
    "- Random Forest Classifier (RFC)\n",
    "- Gradient Boost Classifier (GBC)\n",
    "- Support Vector Machines (SVM)\n",
    "- Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn import metrics \n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.info of        index  having_IPhaving_IP_Address  URLURL_Length  Shortining_Service   \n",
       "4635    4636                           1             -1                   1  \\\n",
       "10638  10639                          -1             -1                   1   \n",
       "10380  10381                          -1             -1                   1   \n",
       "1039    1040                           1             -1                   1   \n",
       "6262    6263                          -1             -1                   1   \n",
       "...      ...                         ...            ...                 ...   \n",
       "2625    2626                           1             -1                   1   \n",
       "10126  10127                          -1             -1                   1   \n",
       "4948    4949                           1             -1                   1   \n",
       "3956    3957                           1             -1                   1   \n",
       "6947    6948                           1             -1                   1   \n",
       "\n",
       "       having_At_Symbol  double_slash_redirecting  Prefix_Suffix   \n",
       "4635                  1                         1             -1  \\\n",
       "10638                -1                         1             -1   \n",
       "10380                 1                         1             -1   \n",
       "1039                  1                         1             -1   \n",
       "6262                  1                         1             -1   \n",
       "...                 ...                       ...            ...   \n",
       "2625                  1                         1             -1   \n",
       "10126                 1                         1             -1   \n",
       "4948                  1                         1             -1   \n",
       "3956                  1                         1             -1   \n",
       "6947                  1                         1             -1   \n",
       "\n",
       "       having_Sub_Domain  SSLfinal_State  Domain_registeration_length  ...   \n",
       "4635                   1               1                           -1  ...  \\\n",
       "10638                 -1              -1                           -1  ...   \n",
       "10380                 -1               0                           -1  ...   \n",
       "1039                   0               1                            1  ...   \n",
       "6262                   1               1                            1  ...   \n",
       "...                  ...             ...                          ...  ...   \n",
       "2625                   0               1                           -1  ...   \n",
       "10126                  1               1                            1  ...   \n",
       "4948                  -1               1                           -1  ...   \n",
       "3956                   0              -1                           -1  ...   \n",
       "6947                   1               1                            1  ...   \n",
       "\n",
       "       popUpWidnow  Iframe  age_of_domain  DNSRecord  web_traffic  Page_Rank   \n",
       "4635             1       1              1          1            1         -1  \\\n",
       "10638            1       1              1          1            0         -1   \n",
       "10380            1       1              1          1            0         -1   \n",
       "1039             1       1              1          1           -1         -1   \n",
       "6262             1       1             -1          1           -1          1   \n",
       "...            ...     ...            ...        ...          ...        ...   \n",
       "2625            -1       1             -1         -1            1         -1   \n",
       "10126           -1      -1             -1          1            0         -1   \n",
       "4948            -1       1              1          1            1         -1   \n",
       "3956             1       1             -1         -1            1         -1   \n",
       "6947             1       1             -1          1           -1          1   \n",
       "\n",
       "       Google_Index  Links_pointing_to_page  Statistical_report  Result  \n",
       "4635              1                       0                   1       1  \n",
       "10638            -1                       0                   1      -1  \n",
       "10380             1                       1                   1      -1  \n",
       "1039              1                       0                   1       1  \n",
       "6262              1                       0                  -1       1  \n",
       "...             ...                     ...                 ...     ...  \n",
       "2625              1                       1                  -1       1  \n",
       "10126            -1                       1                   1       1  \n",
       "4948              1                       0                   1       1  \n",
       "3956              1                       0                   1       1  \n",
       "6947              1                       0                   1       1  \n",
       "\n",
       "[11055 rows x 32 columns]>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = shuffle(pd.read_csv(\"./datasets/dataset.csv\"))\n",
    "\n",
    "df.head\n",
    "df.info\n",
    "\n",
    "#sns.pairplot(df,palette='Dark2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<bound method NDFrame.head of        index  having_IPhaving_IP_Address  URLURL_Length  Shortining_Service   \n",
      "4635    4636                           1             -1                   1  \\\n",
      "10638  10639                          -1             -1                   1   \n",
      "10380  10381                          -1             -1                   1   \n",
      "1039    1040                           1             -1                   1   \n",
      "6262    6263                          -1             -1                   1   \n",
      "...      ...                         ...            ...                 ...   \n",
      "2625    2626                           1             -1                   1   \n",
      "10126  10127                          -1             -1                   1   \n",
      "4948    4949                           1             -1                   1   \n",
      "3956    3957                           1             -1                   1   \n",
      "6947    6948                           1             -1                   1   \n",
      "\n",
      "       having_At_Symbol  double_slash_redirecting  Prefix_Suffix   \n",
      "4635                  1                         1             -1  \\\n",
      "10638                -1                         1             -1   \n",
      "10380                 1                         1             -1   \n",
      "1039                  1                         1             -1   \n",
      "6262                  1                         1             -1   \n",
      "...                 ...                       ...            ...   \n",
      "2625                  1                         1             -1   \n",
      "10126                 1                         1             -1   \n",
      "4948                  1                         1             -1   \n",
      "3956                  1                         1             -1   \n",
      "6947                  1                         1             -1   \n",
      "\n",
      "       having_Sub_Domain  SSLfinal_State  Domain_registeration_length  ...   \n",
      "4635                   1               1                           -1  ...  \\\n",
      "10638                 -1              -1                           -1  ...   \n",
      "10380                 -1               0                           -1  ...   \n",
      "1039                   0               1                            1  ...   \n",
      "6262                   1               1                            1  ...   \n",
      "...                  ...             ...                          ...  ...   \n",
      "2625                   0               1                           -1  ...   \n",
      "10126                  1               1                            1  ...   \n",
      "4948                  -1               1                           -1  ...   \n",
      "3956                   0              -1                           -1  ...   \n",
      "6947                   1               1                            1  ...   \n",
      "\n",
      "       popUpWidnow  Iframe  age_of_domain  DNSRecord  web_traffic  Page_Rank   \n",
      "4635             1       1              1          1            1         -1  \\\n",
      "10638            1       1              1          1            0         -1   \n",
      "10380            1       1              1          1            0         -1   \n",
      "1039             1       1              1          1           -1         -1   \n",
      "6262             1       1             -1          1           -1          1   \n",
      "...            ...     ...            ...        ...          ...        ...   \n",
      "2625            -1       1             -1         -1            1         -1   \n",
      "10126           -1      -1             -1          1            0         -1   \n",
      "4948            -1       1              1          1            1         -1   \n",
      "3956             1       1             -1         -1            1         -1   \n",
      "6947             1       1             -1          1           -1          1   \n",
      "\n",
      "       Google_Index  Links_pointing_to_page  Statistical_report  Result  \n",
      "4635              1                       0                   1       1  \n",
      "10638            -1                       0                   1      -1  \n",
      "10380             1                       1                   1      -1  \n",
      "1039              1                       0                   1       1  \n",
      "6262              1                       0                  -1       1  \n",
      "...             ...                     ...                 ...     ...  \n",
      "2625              1                       1                  -1       1  \n",
      "10126            -1                       1                   1       1  \n",
      "4948              1                       0                   1       1  \n",
      "3956              1                       0                   1       1  \n",
      "6947              1                       0                   1       1  \n",
      "\n",
      "[11055 rows x 32 columns]>\n"
     ]
    }
   ],
   "source": [
    "features = [\n",
    "    \"having_IPhaving_IP_Address\", # URL contains IP\n",
    "    \"URLURL_Length\", # Length of the URL\n",
    "    \"having_At_Symbol\", # URL contains @\n",
    "    \"Shortining_Service\", # Long URL shorted eg. bit.ly...\n",
    "    \"double_slash_redirecting\", # URL contains redirect to another site\n",
    "    \"having_Sub_Domain\", # www.aus.go.au\n",
    "    \"SSLfinal_State\", # URL uses HTTPS\n",
    "    \"Domain_registeration_length\", # URL domain is registed for short period \n",
    "    \"HTTPS_token\", # URL contains http://https\n",
    "    \"Google_Index\", # Can be find via google or not\n",
    "    \"Page_Rank\", # Measures how important a page is on the internet 0 or 1\n",
    "    \"port\", # Scammers open all ports on there server to allow all services\n",
    "    \"Favicon\", # If the favicon is loaded from a domain other than that shown in the address bar - phish\n",
    "    \"Abnormal_URL\", # Fetch by WHOIS database - API\n",
    "    \"age_of_domain\", # Check current domain age\n",
    "    \"DNSRecord\"\n",
    "    ]\n",
    "\n",
    "\n",
    "df.dropna(inplace=True)\n",
    "\n",
    "print(df.head)\n",
    "\n",
    "\n",
    "X = df[features]\n",
    "Y = df[\"Result\"]\n",
    "\n",
    "X.dropna()\n",
    "Y.dropna()\n",
    "\n",
    "X.drop_duplicates()\n",
    "Y.drop_duplicates()\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, Y, train_size=0.8, test_size=0.2, shuffle=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "default_knn = KNeighborsClassifier()\n",
    "default_knn.fit(X_train,y_train)\n",
    "y_pred_knn_default  = default_knn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "estimator = KNeighborsClassifier(algorithm='auto')\n",
    "\n",
    "parameters_KNN = {\n",
    "    'n_neighbors': (1,10, 1),\n",
    "    'leaf_size': (20,40,1),\n",
    "    'p': (1,2),\n",
    "    'weights': ('uniform', 'distance'),\n",
    "    'metric': ('minkowski', 'chebyshev')\n",
    "}\n",
    "grid_search_KNN = GridSearchCV(\n",
    "    estimator=estimator,\n",
    "    param_grid=parameters_KNN,\n",
    "    scoring = 'accuracy',\n",
    "    n_jobs = -1,\n",
    "    cv = 5\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'leaf_size': 20, 'metric': 'minkowski', 'n_neighbors': 10, 'p': 1, 'weights': 'distance'}\n",
      "Best Score - KNN: 0.9017422349206674\n"
     ]
    }
   ],
   "source": [
    "KNN_1=grid_search_KNN.fit(X_train, y_train)\n",
    "y_pred_KNN1 =KNN_1.predict(X_test)\n",
    "KNN_2=grid_search_KNN.fit(X_train, y_train)\n",
    "y_pred_KNN2 =KNN_2.predict(X_test)\n",
    "KNN_3=grid_search_KNN.fit(X_train, y_train)\n",
    "y_pred_KNN3 =KNN_3.predict(X_test)\n",
    "# display the best parameters for KNN classifier\n",
    "print(grid_search_KNN.best_params_ ) \n",
    "# mean cross validated score of the best estimator\n",
    "print('Best Score - KNN:', grid_search_KNN.best_score_ )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy Score - KNN Default: 0.8919041157847128\n",
      "Accuracy Score - KNN_1: 0.9154228855721394\n",
      "Accuracy Score - KNN_2: 0.9154228855721394\n",
      "Accuracy Score - KNN _3:  0.9154228855721394\n"
     ]
    }
   ],
   "source": [
    "print('Accuracy Score - KNN Default:', metrics.accuracy_score(y_test, y_pred_knn_default))  \n",
    "print('Accuracy Score - KNN_1:', metrics.accuracy_score(y_test, y_pred_KNN1)) \n",
    "print('Accuracy Score - KNN_2:', metrics.accuracy_score(y_test, y_pred_KNN2)) \n",
    "print('Accuracy Score - KNN _3: ', metrics.accuracy_score(y_test, y_pred_KNN3)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'leaf_size': 20, 'metric': 'minkowski', 'n_neighbors': 10, 'p': 1, 'weights': 'distance'}\n"
     ]
    }
   ],
   "source": [
    "print(KNN_1.best_params_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "KNN Evaluation Complete\n",
    "==="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'bootstrap': True, 'ccp_alpha': 0.0, 'criterion': 'squared_error', 'max_depth': None, 'max_features': 1.0, 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 100, 'n_jobs': None, 'oob_score': False, 'random_state': 42, 'verbose': 0, 'warm_start': False}\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "rfr_default = RandomForestRegressor(random_state=42)\n",
    "print(rfr_default.get_params())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "n_estimators = number of trees in random forest\n",
    "max_features = number of features consider in each split\n",
    "max_depth = maximum number of levels within the tree\n",
    "min_samples_split = samples required at each split node\n",
    "min_samples_leaf = minimum number if leafs at each node\n",
    "boostrap = selecting training method at each level\n",
    "'''\n",
    "n_estimators = [int(x) for x in np.linspace(start = 200, stop = 2000, num = 10)]\n",
    "max_features = ['auto', 'sqrt']\n",
    "max_depth = [int(x) for x in np.linspace(10, 110, num = 11)]\n",
    "max_depth.append(None)\n",
    "min_samples_split = [2, 5, 10]\n",
    "min_samples_leaf = [1, 2, 4]\n",
    "bootstrap = [True, False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "parameters_RFR = {\n",
    "    'n_estimators': n_estimators,\n",
    "    'max_features': max_features,\n",
    "    'max_depth': max_depth,\n",
    "    'min_samples_split': min_samples_split,\n",
    "    'min_samples_leaf': min_samples_leaf,\n",
    "    'bootstrap': bootstrap\n",
    "    }\n",
    "\n",
    "grid_search_RFR = GridSearchCV(\n",
    "    estimator=rfr_default,\n",
    "    param_grid=parameters_RFR,\n",
    "    scoring='f1',\n",
    "    n_jobs=-1,\n",
    "    cv=5,\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:778: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: \n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 767, in _score\n",
      "    scores = scorer(estimator, X_test, y_test)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 234, in __call__\n",
      "    return self._score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_scorer.py\", line 282, in _score\n",
      "    return self._sign * self._score_func(y_true, y_pred, **self._kwargs)\n",
      "                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1146, in f1_score\n",
      "    return fbeta_score(\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1287, in fbeta_score\n",
      "    _, _, f, _ = precision_recall_fscore_support(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1573, in precision_recall_fscore_support\n",
      "    labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 1374, in _check_set_wise_labels\n",
      "    y_type, y_true, y_pred = _check_targets(y_true, y_pred)\n",
      "                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/metrics/_classification.py\", line 95, in _check_targets\n",
      "    raise ValueError(\n",
      "ValueError: Classification metrics can't handle a mix of binary and continuous targets\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/ensemble/_forest.py:413: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
      "  warn(\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[35], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m RFR_1 \u001b[38;5;241m=\u001b[39m \u001b[43mgrid_search_RFR\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_train\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m y_pred_RFR1 \u001b[38;5;241m=\u001b[39m RFR_1\u001b[38;5;241m.\u001b[39mpredict(X_test)\n\u001b[1;32m      3\u001b[0m RFR_2 \u001b[38;5;241m=\u001b[39m grid_search_RFR\u001b[38;5;241m.\u001b[39mfit(X_train, y_train)\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_search.py:874\u001b[0m, in \u001b[0;36mBaseSearchCV.fit\u001b[0;34m(self, X, y, groups, **fit_params)\u001b[0m\n\u001b[1;32m    868\u001b[0m     results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_format_results(\n\u001b[1;32m    869\u001b[0m         all_candidate_params, n_splits, all_out, all_more_results\n\u001b[1;32m    870\u001b[0m     )\n\u001b[1;32m    872\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m results\n\u001b[0;32m--> 874\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_run_search\u001b[49m\u001b[43m(\u001b[49m\u001b[43mevaluate_candidates\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    876\u001b[0m \u001b[38;5;66;03m# multimetric is determined here because in the case of a callable\u001b[39;00m\n\u001b[1;32m    877\u001b[0m \u001b[38;5;66;03m# self.scoring the return type is only known after calling\u001b[39;00m\n\u001b[1;32m    878\u001b[0m first_test_score \u001b[38;5;241m=\u001b[39m all_out[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtest_scores\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_search.py:1388\u001b[0m, in \u001b[0;36mGridSearchCV._run_search\u001b[0;34m(self, evaluate_candidates)\u001b[0m\n\u001b[1;32m   1386\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_run_search\u001b[39m(\u001b[38;5;28mself\u001b[39m, evaluate_candidates):\n\u001b[1;32m   1387\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Search all candidates in param_grid\"\"\"\u001b[39;00m\n\u001b[0;32m-> 1388\u001b[0m     \u001b[43mevaluate_candidates\u001b[49m\u001b[43m(\u001b[49m\u001b[43mParameterGrid\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparam_grid\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_search.py:821\u001b[0m, in \u001b[0;36mBaseSearchCV.fit.<locals>.evaluate_candidates\u001b[0;34m(candidate_params, cv, more_results)\u001b[0m\n\u001b[1;32m    813\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mverbose \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m    814\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\n\u001b[1;32m    815\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFitting \u001b[39m\u001b[38;5;132;01m{0}\u001b[39;00m\u001b[38;5;124m folds for each of \u001b[39m\u001b[38;5;132;01m{1}\u001b[39;00m\u001b[38;5;124m candidates,\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    816\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m totalling \u001b[39m\u001b[38;5;132;01m{2}\u001b[39;00m\u001b[38;5;124m fits\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m    817\u001b[0m             n_splits, n_candidates, n_candidates \u001b[38;5;241m*\u001b[39m n_splits\n\u001b[1;32m    818\u001b[0m         )\n\u001b[1;32m    819\u001b[0m     )\n\u001b[0;32m--> 821\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[43mparallel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    822\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdelayed\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_fit_and_score\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    823\u001b[0m \u001b[43m        \u001b[49m\u001b[43mclone\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbase_estimator\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    824\u001b[0m \u001b[43m        \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    825\u001b[0m \u001b[43m        \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    826\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtrain\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    827\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtest\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    828\u001b[0m \u001b[43m        \u001b[49m\u001b[43mparameters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparameters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    829\u001b[0m \u001b[43m        \u001b[49m\u001b[43msplit_progress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43msplit_idx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_splits\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    830\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcandidate_progress\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcand_idx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_candidates\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    831\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfit_and_score_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    832\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    833\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mcand_idx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparameters\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43msplit_idx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtest\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mproduct\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    834\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcandidate_params\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcv\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msplit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgroups\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    835\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    836\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    838\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(out) \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m    839\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    840\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo fits were performed. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    841\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mWas the CV iterator empty? \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    842\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mWere there no candidates?\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    843\u001b[0m     )\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/utils/parallel.py:63\u001b[0m, in \u001b[0;36mParallel.__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m     58\u001b[0m config \u001b[38;5;241m=\u001b[39m get_config()\n\u001b[1;32m     59\u001b[0m iterable_with_config \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m     60\u001b[0m     (_with_config(delayed_func, config), args, kwargs)\n\u001b[1;32m     61\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m delayed_func, args, kwargs \u001b[38;5;129;01min\u001b[39;00m iterable\n\u001b[1;32m     62\u001b[0m )\n\u001b[0;32m---> 63\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__call__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43miterable_with_config\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/joblib/parallel.py:1944\u001b[0m, in \u001b[0;36mParallel.__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m   1938\u001b[0m \u001b[38;5;66;03m# The first item from the output is blank, but it makes the interpreter\u001b[39;00m\n\u001b[1;32m   1939\u001b[0m \u001b[38;5;66;03m# progress until it enters the Try/Except block of the generator and\u001b[39;00m\n\u001b[1;32m   1940\u001b[0m \u001b[38;5;66;03m# reach the first `yield` statement. This starts the aynchronous\u001b[39;00m\n\u001b[1;32m   1941\u001b[0m \u001b[38;5;66;03m# dispatch of the tasks to the workers.\u001b[39;00m\n\u001b[1;32m   1942\u001b[0m \u001b[38;5;28mnext\u001b[39m(output)\n\u001b[0;32m-> 1944\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreturn_generator \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43moutput\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/joblib/parallel.py:1587\u001b[0m, in \u001b[0;36mParallel._get_outputs\u001b[0;34m(self, iterator, pre_dispatch)\u001b[0m\n\u001b[1;32m   1584\u001b[0m     \u001b[38;5;28;01myield\u001b[39;00m\n\u001b[1;32m   1586\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backend\u001b[38;5;241m.\u001b[39mretrieval_context():\n\u001b[0;32m-> 1587\u001b[0m         \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_retrieve()\n\u001b[1;32m   1589\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mGeneratorExit\u001b[39;00m:\n\u001b[1;32m   1590\u001b[0m     \u001b[38;5;66;03m# The generator has been garbage collected before being fully\u001b[39;00m\n\u001b[1;32m   1591\u001b[0m     \u001b[38;5;66;03m# consumed. This aborts the remaining tasks if possible and warn\u001b[39;00m\n\u001b[1;32m   1592\u001b[0m     \u001b[38;5;66;03m# the user if necessary.\u001b[39;00m\n\u001b[1;32m   1593\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_exception \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/joblib/parallel.py:1699\u001b[0m, in \u001b[0;36mParallel._retrieve\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1694\u001b[0m \u001b[38;5;66;03m# If the next job is not ready for retrieval yet, we just wait for\u001b[39;00m\n\u001b[1;32m   1695\u001b[0m \u001b[38;5;66;03m# async callbacks to progress.\u001b[39;00m\n\u001b[1;32m   1696\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ((\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jobs) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m\n\u001b[1;32m   1697\u001b[0m     (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jobs[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mget_status(\n\u001b[1;32m   1698\u001b[0m         timeout\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtimeout) \u001b[38;5;241m==\u001b[39m TASK_PENDING)):\n\u001b[0;32m-> 1699\u001b[0m     time\u001b[38;5;241m.\u001b[39msleep(\u001b[38;5;241m0.01\u001b[39m)\n\u001b[1;32m   1700\u001b[0m     \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[1;32m   1702\u001b[0m \u001b[38;5;66;03m# We need to be careful: the job list can be filling up as\u001b[39;00m\n\u001b[1;32m   1703\u001b[0m \u001b[38;5;66;03m# we empty it and Python list are not thread-safe by\u001b[39;00m\n\u001b[1;32m   1704\u001b[0m \u001b[38;5;66;03m# default hence the use of the lock\u001b[39;00m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "RFR_1 = grid_search_RFR.fit(X_train, y_train)\n",
    "y_pred_RFR1 = RFR_1.predict(X_test)\n",
    "RFR_2 = grid_search_RFR.fit(X_train, y_train)\n",
    "y_pred_RFR2 = RFR_2.predict(X_test)\n",
    "RFR_3 = grid_search_RFR.fit(X_train, y_train)\n",
    "y_pred_RFR3 = KNN_3.predict(X_test)\n",
    "print(grid_search_RFR.best_params_ ) \n",
    "print('Best Score - RFR:', grid_search_RFR.best_score_ )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Issue with KNN model moving to SVM\n",
    "==="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "poly\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "          -1       0.87      0.81      0.84       954\n",
      "           1       0.86      0.91      0.88      1257\n",
      "\n",
      "    accuracy                           0.86      2211\n",
      "   macro avg       0.86      0.86      0.86      2211\n",
      "weighted avg       0.86      0.86      0.86      2211\n",
      "\n",
      "rbf\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "          -1       0.88      0.85      0.87       980\n",
      "           1       0.88      0.91      0.90      1231\n",
      "\n",
      "    accuracy                           0.88      2211\n",
      "   macro avg       0.88      0.88      0.88      2211\n",
      "weighted avg       0.88      0.88      0.88      2211\n",
      "\n",
      "sigmoid\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "          -1       0.69      0.70      0.70       988\n",
      "           1       0.76      0.75      0.75      1223\n",
      "\n",
      "    accuracy                           0.73      2211\n",
      "   macro avg       0.72      0.72      0.72      2211\n",
      "weighted avg       0.73      0.73      0.73      2211\n",
      "\n",
      "linear\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "          -1       0.89      0.84      0.86       969\n",
      "           1       0.88      0.92      0.90      1242\n",
      "\n",
      "    accuracy                           0.88      2211\n",
      "   macro avg       0.88      0.88      0.88      2211\n",
      "weighted avg       0.88      0.88      0.88      2211\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.svm import SVC, LinearSVC\n",
    "from sklearn.metrics import classification_report, confusion_matrix  \n",
    "\n",
    "# Different kernels allow different approaches to transforming data into the required form\n",
    "kernels = [\"poly\", \"rbf\", \"sigmoid\", \"linear\"]\n",
    "for i in range(len(kernels)):\n",
    "    # new set every iteration\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size = 0.20, shuffle=True)\n",
    "    if i == 0: svm_classifier = SVC(kernel=kernels[i],degree=2,gamma=\"auto\")\n",
    "    else: svm_classifier = SVC(kernel=kernels[i],gamma=\"auto\")\n",
    "    svm_classifier.fit(X_train, y_train)\n",
    "    y_pred = svm_classifier.predict(X_test)\n",
    "    print(kernels[i])\n",
    "    print(classification_report(y_test, y_pred))\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 720 candidates, totalling 3600 fits\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.01, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.1s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.3s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=0.1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.3s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.3s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.3s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.3s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.2s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.2s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.5s[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=1, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.1s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.1s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.3s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.2s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.3s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.3s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.9s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.6s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.6s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
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      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
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      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.1s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.2s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.6s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.5s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.6s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.0s\n",
      "[CV] END C=10, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.6s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.9s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.6s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.5s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.6s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.3s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.9s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.9s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.9s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.5s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.6s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.2s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.1s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.2s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.9s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.3s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.2s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.9s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.2s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.5s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=10, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=10, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.9s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.3s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.2s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.6s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.6s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.6s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=None, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.6s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.6s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.3s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.7s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.3s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.5s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.4s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=None, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.1s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.7s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.8s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.2s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.1s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=1000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=2000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l1, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=0.0001; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=False, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.0s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.3s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.2s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   1.2s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py:1244: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py:378: FitFailedWarning: \n",
      "1800 fits failed out of a total of 3600.\n",
      "The score on these train-test partitions for these parameters will be set to nan.\n",
      "If these failures are not expected, you can try to debug them by setting error_score='raise'.\n",
      "\n",
      "Below are more details about the failures:\n",
      "--------------------------------------------------------------------------------\n",
      "450 fits failed with the following error:\n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score\n",
      "    estimator.fit(X_train, y_train, **fit_params)\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_classes.py\", line 274, in fit\n",
      "    self.coef_, self.intercept_, n_iter_ = _fit_liblinear(\n",
      "                                           ^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py\", line 1223, in _fit_liblinear\n",
      "    solver_type = _get_liblinear_solver_type(multi_class, penalty, loss, dual)\n",
      "                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py\", line 1062, in _get_liblinear_solver_type\n",
      "    raise ValueError(\n",
      "ValueError: Unsupported set of arguments: The combination of penalty='l1' and loss='hinge' is not supported, Parameters: penalty='l1', loss='hinge', dual=True\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "450 fits failed with the following error:\n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score\n",
      "    estimator.fit(X_train, y_train, **fit_params)\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_classes.py\", line 274, in fit\n",
      "    self.coef_, self.intercept_, n_iter_ = _fit_liblinear(\n",
      "                                           ^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py\", line 1223, in _fit_liblinear\n",
      "    solver_type = _get_liblinear_solver_type(multi_class, penalty, loss, dual)\n",
      "                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py\", line 1062, in _get_liblinear_solver_type\n",
      "    raise ValueError(\n",
      "ValueError: Unsupported set of arguments: The combination of penalty='l1' and loss='squared_hinge' are not supported when dual=True, Parameters: penalty='l1', loss='squared_hinge', dual=True\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "450 fits failed with the following error:\n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score\n",
      "    estimator.fit(X_train, y_train, **fit_params)\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_classes.py\", line 274, in fit\n",
      "    self.coef_, self.intercept_, n_iter_ = _fit_liblinear(\n",
      "                                           ^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py\", line 1223, in _fit_liblinear\n",
      "    solver_type = _get_liblinear_solver_type(multi_class, penalty, loss, dual)\n",
      "                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py\", line 1062, in _get_liblinear_solver_type\n",
      "    raise ValueError(\n",
      "ValueError: Unsupported set of arguments: The combination of penalty='l1' and loss='hinge' is not supported, Parameters: penalty='l1', loss='hinge', dual=False\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "450 fits failed with the following error:\n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_validation.py\", line 686, in _fit_and_score\n",
      "    estimator.fit(X_train, y_train, **fit_params)\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_classes.py\", line 274, in fit\n",
      "    self.coef_, self.intercept_, n_iter_ = _fit_liblinear(\n",
      "                                           ^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py\", line 1223, in _fit_liblinear\n",
      "    solver_type = _get_liblinear_solver_type(multi_class, penalty, loss, dual)\n",
      "                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/svm/_base.py\", line 1062, in _get_liblinear_solver_type\n",
      "    raise ValueError(\n",
      "ValueError: Unsupported set of arguments: The combination of penalty='l2' and loss='hinge' are not supported when dual=False, Parameters: penalty='l2', loss='hinge', dual=False\n",
      "\n",
      "  warnings.warn(some_fits_failed_message, FitFailedWarning)\n",
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_search.py:952: UserWarning: One or more of the test scores are non-finite: [       nan        nan        nan 0.88523394 0.88726906 0.88478222\n",
      "        nan        nan        nan 0.88489573 0.8871567  0.88478165\n",
      "        nan        nan        nan 0.88806053 0.87777242 0.88602567\n",
      "        nan        nan        nan 0.86816055 0.86816055 0.86816055\n",
      "        nan        nan        nan 0.86816055 0.86816055 0.86816055\n",
      "        nan        nan        nan 0.86816055 0.86816055 0.86816055\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.86759526 0.86804749 0.86804749 0.86816055 0.86816055 0.86816055\n",
      " 0.86804749 0.86804749 0.86804749 0.86816055 0.86816055 0.86816055\n",
      " 0.86759526 0.86804749 0.86804749 0.86816055 0.86816055 0.86816055\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.87358786 0.87358786 0.87358786\n",
      "        nan        nan        nan 0.87358786 0.87358786 0.87358786\n",
      "        nan        nan        nan 0.87358786 0.87358786 0.87358786\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.87844962 0.87844962 0.87844962 0.87358786 0.87358786 0.87358786\n",
      " 0.87844962 0.87844962 0.87844962 0.87358786 0.87358786 0.87358786\n",
      " 0.87844962 0.87844962 0.87844962 0.87358786 0.87358786 0.87358786\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.86872597 0.86872597 0.86872597 0.86883903 0.86883903 0.86883903\n",
      " 0.86872597 0.86872597 0.86872597 0.86883903 0.86883903 0.86883903\n",
      " 0.86872597 0.86872597 0.86872597 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan 0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan 0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.87404009 0.87426621 0.87426621 0.8743792  0.8743792  0.8743792\n",
      " 0.87426621 0.87426621 0.87426621 0.8743792  0.8743792  0.8743792\n",
      " 0.87415315 0.87426621 0.87426621 0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan 0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan 0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.87426614 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792\n",
      " 0.87426614 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792\n",
      " 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.86838648 0.86827355 0.87064777\n",
      "        nan        nan        nan 0.86883903 0.86883903 0.86872597\n",
      "        nan        nan        nan 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.87381385 0.87381462 0.87358773\n",
      "        nan        nan        nan 0.87426614 0.8743792  0.87415309\n",
      "        nan        nan        nan 0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792  0.8743792\n",
      " 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792  0.8743792\n",
      " 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792  0.8743792\n",
      "        nan        nan        nan 0.83673056 0.77826974 0.82530304\n",
      "        nan        nan        nan 0.88579923 0.88896582 0.88376495\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.82361075 0.77679787 0.76074699\n",
      "        nan        nan        nan 0.84667764 0.83966943 0.83186733\n",
      "        nan        nan        nan 0.856516   0.84893982 0.85606025\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      " 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903 0.86883903\n",
      "        nan        nan        nan 0.81499786 0.85493197 0.79217909\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.89032259 0.89032259 0.89032259\n",
      "        nan        nan        nan 0.81604205 0.79613223 0.80008319\n",
      "        nan        nan        nan 0.85176737 0.84746955 0.8310763\n",
      "        nan        nan        nan 0.84283193 0.84418952 0.86329764\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      "        nan        nan        nan        nan        nan        nan\n",
      " 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792  0.8743792\n",
      " 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792  0.8743792\n",
      " 0.8743792  0.8743792  0.8743792  0.8743792  0.8743792  0.8743792 ]\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.9s\n",
      "[CV] END C=100, class_weight=balanced, dual=True, loss=squared_hinge, max_iter=3000, penalty=l2, tol=1e-05; total time=   0.9s\n"
     ]
    },
    {
     "data": {
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       "<style>#sk-container-id-3 {color: black;background-color: white;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=5, estimator=LinearSVC(), n_jobs=-1,\n",
       "             param_grid={&#x27;C&#x27;: [0.01, 0.1, 1, 10, 100],\n",
       "                         &#x27;class_weight&#x27;: [None, &#x27;balanced&#x27;],\n",
       "                         &#x27;dual&#x27;: [True, False],\n",
       "                         &#x27;loss&#x27;: [&#x27;hinge&#x27;, &#x27;squared_hinge&#x27;],\n",
       "                         &#x27;max_iter&#x27;: [1000, 2000, 3000],\n",
       "                         &#x27;penalty&#x27;: [&#x27;l1&#x27;, &#x27;l2&#x27;],\n",
       "                         &#x27;tol&#x27;: [0.001, 0.0001, 1e-05]},\n",
       "             verbose=2)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GridSearchCV</label><div class=\"sk-toggleable__content\"><pre>GridSearchCV(cv=5, estimator=LinearSVC(), n_jobs=-1,\n",
       "             param_grid={&#x27;C&#x27;: [0.01, 0.1, 1, 10, 100],\n",
       "                         &#x27;class_weight&#x27;: [None, &#x27;balanced&#x27;],\n",
       "                         &#x27;dual&#x27;: [True, False],\n",
       "                         &#x27;loss&#x27;: [&#x27;hinge&#x27;, &#x27;squared_hinge&#x27;],\n",
       "                         &#x27;max_iter&#x27;: [1000, 2000, 3000],\n",
       "                         &#x27;penalty&#x27;: [&#x27;l1&#x27;, &#x27;l2&#x27;],\n",
       "                         &#x27;tol&#x27;: [0.001, 0.0001, 1e-05]},\n",
       "             verbose=2)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: LinearSVC</label><div class=\"sk-toggleable__content\"><pre>LinearSVC()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LinearSVC</label><div class=\"sk-toggleable__content\"><pre>LinearSVC()</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=5, estimator=LinearSVC(), n_jobs=-1,\n",
       "             param_grid={'C': [0.01, 0.1, 1, 10, 100],\n",
       "                         'class_weight': [None, 'balanced'],\n",
       "                         'dual': [True, False],\n",
       "                         'loss': ['hinge', 'squared_hinge'],\n",
       "                         'max_iter': [1000, 2000, 3000],\n",
       "                         'penalty': ['l1', 'l2'],\n",
       "                         'tol': [0.001, 0.0001, 1e-05]},\n",
       "             verbose=2)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linear_svc = LinearSVC()\n",
    "linear_svc.fit(X_train, y_train)\n",
    "lin_pred = linear_svc.predict(X_test)\n",
    "\n",
    "params = {\n",
    "    'C': [0.01, 0.1, 1, 10, 100],\n",
    "    'penalty': ['l1', 'l2'],\n",
    "    'loss': ['hinge', 'squared_hinge'],\n",
    "    'dual': [True, False],\n",
    "    'tol': [1e-3, 1e-4, 1e-5],\n",
    "    'max_iter': [1000, 2000, 3000],\n",
    "    'class_weight': [None, 'balanced']\n",
    "}\n",
    "svc_grid_search = GridSearchCV(estimator=linear_svc, param_grid=params, \n",
    "                           cv=5, n_jobs=-1, verbose=2)\n",
    "svc_grid_search.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'C': 0.01, 'class_weight': 'balanced', 'dual': True, 'loss': 'hinge', 'max_iter': 1000, 'penalty': 'l2', 'tol': 0.001}\n",
      "LinearSVC(C=0.01, class_weight='balanced', loss='hinge', tol=0.001)\n",
      "0.8833107191316146\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/levi_1/Library/Python/3.11/lib/python/site-packages/sklearn/base.py:439: UserWarning: X does not have valid feature names, but LinearSVC was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "X has 13 features, but LinearSVC is expecting 16 features as input.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[38], line 5\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28mprint\u001b[39m(svc_grid_search\u001b[38;5;241m.\u001b[39mbest_estimator_)\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28mprint\u001b[39m(svc_grid_search\u001b[38;5;241m.\u001b[39mscore(X_test,y_test))\n\u001b[0;32m----> 5\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43msvc_grid_search\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m42\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m)\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/model_selection/_search.py:499\u001b[0m, in \u001b[0;36mBaseSearchCV.predict\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    481\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Call predict on the estimator with the best found parameters.\u001b[39;00m\n\u001b[1;32m    482\u001b[0m \n\u001b[1;32m    483\u001b[0m \u001b[38;5;124;03mOnly available if ``refit=True`` and the underlying estimator supports\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    496\u001b[0m \u001b[38;5;124;03m    the best found parameters.\u001b[39;00m\n\u001b[1;32m    497\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    498\u001b[0m check_is_fitted(\u001b[38;5;28mself\u001b[39m)\n\u001b[0;32m--> 499\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbest_estimator_\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/linear_model/_base.py:419\u001b[0m, in \u001b[0;36mLinearClassifierMixin.predict\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    405\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    406\u001b[0m \u001b[38;5;124;03mPredict class labels for samples in X.\u001b[39;00m\n\u001b[1;32m    407\u001b[0m \n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    416\u001b[0m \u001b[38;5;124;03m    Vector containing the class labels for each sample.\u001b[39;00m\n\u001b[1;32m    417\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    418\u001b[0m xp, _ \u001b[38;5;241m=\u001b[39m get_namespace(X)\n\u001b[0;32m--> 419\u001b[0m scores \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecision_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    420\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(scores\u001b[38;5;241m.\u001b[39mshape) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m    421\u001b[0m     indices \u001b[38;5;241m=\u001b[39m xp\u001b[38;5;241m.\u001b[39mastype(scores \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mint\u001b[39m)\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/linear_model/_base.py:400\u001b[0m, in \u001b[0;36mLinearClassifierMixin.decision_function\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    397\u001b[0m check_is_fitted(\u001b[38;5;28mself\u001b[39m)\n\u001b[1;32m    398\u001b[0m xp, _ \u001b[38;5;241m=\u001b[39m get_namespace(X)\n\u001b[0;32m--> 400\u001b[0m X \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maccept_sparse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcsr\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mreset\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m    401\u001b[0m scores \u001b[38;5;241m=\u001b[39m safe_sparse_dot(X, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcoef_\u001b[38;5;241m.\u001b[39mT, dense_output\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mintercept_\n\u001b[1;32m    402\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m xp\u001b[38;5;241m.\u001b[39mreshape(scores, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m) \u001b[38;5;28;01mif\u001b[39;00m scores\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m scores\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/base.py:588\u001b[0m, in \u001b[0;36mBaseEstimator._validate_data\u001b[0;34m(self, X, y, reset, validate_separately, **check_params)\u001b[0m\n\u001b[1;32m    585\u001b[0m     out \u001b[38;5;241m=\u001b[39m X, y\n\u001b[1;32m    587\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m no_val_X \u001b[38;5;129;01mand\u001b[39;00m check_params\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mensure_2d\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[0;32m--> 588\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_check_n_features\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mreset\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreset\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    590\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\n",
      "File \u001b[0;32m~/Library/Python/3.11/lib/python/site-packages/sklearn/base.py:389\u001b[0m, in \u001b[0;36mBaseEstimator._check_n_features\u001b[0;34m(self, X, reset)\u001b[0m\n\u001b[1;32m    386\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m    388\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n_features \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_features_in_:\n\u001b[0;32m--> 389\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    390\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mX has \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mn_features\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m features, but \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    391\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis expecting \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_features_in_\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m features as input.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    392\u001b[0m     )\n",
      "\u001b[0;31mValueError\u001b[0m: X has 13 features, but LinearSVC is expecting 16 features as input."
     ]
    }
   ],
   "source": [
    "print(svc_grid_search.best_params_)\n",
    "print(svc_grid_search.best_estimator_)\n",
    "print(svc_grid_search.score(X_test,y_test))\n",
    "\n",
    "print(svc_grid_search.predict([[42,0,0,0,0,0,2,0,0,3,0,0,0]]))"
   ]
  }
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