credit_risk_analysis_ML.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "x9MnCTHFMSB9"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import precision_score, recall_score, accuracy_score\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import  cross_val_predict\n",
    "import pandas as pd \n",
    "from sklearn.feature_selection import RFECV\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn import metrics\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.preprocessing import minmax_scale\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "import tensorflow as tf\n",
    "import warnings\n",
    "import matplotlib.gridspec as gridspec\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn import preprocessing\n",
    "from sklearn.manifold import TSNE\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "from scipy import stats\n",
    "from scipy.stats import shapiro\n",
    "from scipy.stats import anderson\n",
    "from sklearn.model_selection import train_test_split\n",
    "from scipy.stats import mannwhitneyu\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from imblearn.over_sampling import RandomOverSampler\n",
    "from imblearn.under_sampling import RandomUnderSampler\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "from sklearn.decomposition import PCA\n",
    "from imblearn.under_sampling import TomekLinks\n",
    "from imblearn.over_sampling import SMOTE\n",
    "from imblearn.under_sampling import ClusterCentroids\n",
    "from imblearn.pipeline import make_pipeline\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "oph15p7FM042",
    "outputId": "b1035660-7d62-48b9-c2f0-2631015b6cda"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drive already mounted at /gdrive; to attempt to forcibly remount, call drive.mount(\"/gdrive\", force_remount=True).\n",
      "/gdrive\n"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/gdrive')\n",
    "%cd /gdrive"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LOADING THE DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "n5cMl0XgNKqf",
    "outputId": "fa1332bc-8846-4823-f723-1118c4a45a4a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 42538 entries, 0 to 42537\n",
      "Data columns (total 52 columns):\n",
      "id                            42538 non-null object\n",
      "member_id                     42535 non-null float64\n",
      "loan_amnt                     42535 non-null float64\n",
      "funded_amnt                   42535 non-null float64\n",
      "funded_amnt_inv               42535 non-null float64\n",
      "term                          42535 non-null object\n",
      "int_rate                      42535 non-null object\n",
      "installment                   42535 non-null float64\n",
      "grade                         42535 non-null object\n",
      "sub_grade                     42535 non-null object\n",
      "emp_title                     39909 non-null object\n",
      "emp_length                    41423 non-null object\n",
      "home_ownership                42535 non-null object\n",
      "annual_inc                    42531 non-null float64\n",
      "verification_status           42535 non-null object\n",
      "issue_d                       42535 non-null object\n",
      "loan_status                   42535 non-null object\n",
      "pymnt_plan                    42535 non-null object\n",
      "purpose                       42535 non-null object\n",
      "title                         42522 non-null object\n",
      "zip_code                      42535 non-null object\n",
      "addr_state                    42535 non-null object\n",
      "dti                           42535 non-null float64\n",
      "delinq_2yrs                   42506 non-null float64\n",
      "earliest_cr_line              42506 non-null object\n",
      "inq_last_6mths                42506 non-null float64\n",
      "open_acc                      42506 non-null float64\n",
      "pub_rec                       42506 non-null float64\n",
      "revol_bal                     42535 non-null float64\n",
      "revol_util                    42445 non-null object\n",
      "total_acc                     42506 non-null float64\n",
      "initial_list_status           42535 non-null object\n",
      "out_prncp                     42535 non-null float64\n",
      "out_prncp_inv                 42535 non-null float64\n",
      "total_pymnt                   42535 non-null float64\n",
      "total_pymnt_inv               42535 non-null float64\n",
      "total_rec_prncp               42535 non-null float64\n",
      "total_rec_int                 42535 non-null float64\n",
      "total_rec_late_fee            42535 non-null float64\n",
      "recoveries                    42535 non-null float64\n",
      "collection_recovery_fee       42535 non-null float64\n",
      "last_pymnt_d                  42452 non-null object\n",
      "last_pymnt_amnt               42535 non-null float64\n",
      "last_credit_pull_d            42531 non-null object\n",
      "collections_12_mths_ex_med    42390 non-null float64\n",
      "policy_code                   42535 non-null float64\n",
      "application_type              42535 non-null object\n",
      "acc_now_delinq                42506 non-null float64\n",
      "chargeoff_within_12_mths      42390 non-null float64\n",
      "delinq_amnt                   42506 non-null float64\n",
      "pub_rec_bankruptcies          41170 non-null float64\n",
      "tax_liens                     42430 non-null float64\n",
      "dtypes: float64(30), object(22)\n",
      "memory usage: 16.9+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "data = pd.read_csv('/gdrive/My Drive/files/loans_2007.csv')\n",
    "print(data.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 255
    },
    "colab_type": "code",
    "id": "5kEd7QDEd0zq",
    "outputId": "d0965966-7622-476e-fee0-9a9caee8156f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'member_id', 'loan_amnt', 'funded_amnt', 'funded_amnt_inv',\n",
       "       'term', 'int_rate', 'installment', 'grade', 'sub_grade', 'emp_title',\n",
       "       'emp_length', 'home_ownership', 'annual_inc', 'verification_status',\n",
       "       'issue_d', 'loan_status', 'pymnt_plan', 'purpose', 'title', 'zip_code',\n",
       "       'addr_state', 'dti', 'delinq_2yrs', 'earliest_cr_line',\n",
       "       'inq_last_6mths', 'open_acc', 'pub_rec', 'revol_bal', 'revol_util',\n",
       "       'total_acc', 'initial_list_status', 'out_prncp', 'out_prncp_inv',\n",
       "       'total_pymnt', 'total_pymnt_inv', 'total_rec_prncp', 'total_rec_int',\n",
       "       'total_rec_late_fee', 'recoveries', 'collection_recovery_fee',\n",
       "       'last_pymnt_d', 'last_pymnt_amnt', 'last_credit_pull_d',\n",
       "       'collections_12_mths_ex_med', 'policy_code', 'application_type',\n",
       "       'acc_now_delinq', 'chargeoff_within_12_mths', 'delinq_amnt',\n",
       "       'pub_rec_bankruptcies', 'tax_liens'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FEATURE ENGINEERING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "jlVSkEOkdwCc"
   },
   "outputs": [],
   "source": [
    "data = data.drop(columns=['id', 'member_id','funded_amnt', 'funded_amnt_inv','sub_grade','emp_title','issue_d','total_pymnt', 'total_pymnt_inv', 'total_rec_prncp','out_prncp', 'out_prncp_inv','zip_code', 'total_rec_prncp', 'total_rec_int',\n",
    "       'total_rec_late_fee', 'recoveries', 'collection_recovery_fee',\n",
    "       'last_pymnt_d', 'last_pymnt_amnt'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 663
    },
    "colab_type": "code",
    "id": "z9sUmeoyfehn",
    "outputId": "dcc85334-fc28-4525-e870-bdf60c221ece"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 42538 entries, 0 to 42537\n",
      "Data columns (total 33 columns):\n",
      "loan_amnt                     42535 non-null float64\n",
      "term                          42535 non-null object\n",
      "int_rate                      42535 non-null object\n",
      "installment                   42535 non-null float64\n",
      "grade                         42535 non-null object\n",
      "emp_length                    41423 non-null object\n",
      "home_ownership                42535 non-null object\n",
      "annual_inc                    42531 non-null float64\n",
      "verification_status           42535 non-null object\n",
      "loan_status                   42535 non-null object\n",
      "pymnt_plan                    42535 non-null object\n",
      "purpose                       42535 non-null object\n",
      "title                         42522 non-null object\n",
      "addr_state                    42535 non-null object\n",
      "dti                           42535 non-null float64\n",
      "delinq_2yrs                   42506 non-null float64\n",
      "earliest_cr_line              42506 non-null object\n",
      "inq_last_6mths                42506 non-null float64\n",
      "open_acc                      42506 non-null float64\n",
      "pub_rec                       42506 non-null float64\n",
      "revol_bal                     42535 non-null float64\n",
      "revol_util                    42445 non-null object\n",
      "total_acc                     42506 non-null float64\n",
      "initial_list_status           42535 non-null object\n",
      "last_credit_pull_d            42531 non-null object\n",
      "collections_12_mths_ex_med    42390 non-null float64\n",
      "policy_code                   42535 non-null float64\n",
      "application_type              42535 non-null object\n",
      "acc_now_delinq                42506 non-null float64\n",
      "chargeoff_within_12_mths      42390 non-null float64\n",
      "delinq_amnt                   42506 non-null float64\n",
      "pub_rec_bankruptcies          41170 non-null float64\n",
      "tax_liens                     42430 non-null float64\n",
      "dtypes: float64(17), object(16)\n",
      "memory usage: 10.7+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 765
    },
    "colab_type": "code",
    "id": "U_MJ2mbkhiGs",
    "outputId": "26d87d17-1320-4897-d6b6-6b77b12202be"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   loan_amnt        term int_rate  installment grade\n",
      "0     5000.0   36 months   10.65%       162.87     B\n",
      "1     2500.0   60 months   15.27%        59.83     C\n",
      "2     2400.0   36 months   15.96%        84.33     C\n",
      "3    10000.0   36 months   13.49%       339.31     C\n",
      "4     3000.0   60 months   12.69%        67.79     B\n",
      "  emp_length home_ownership  annual_inc verification_status  loan_status\n",
      "0  10+ years           RENT     24000.0            Verified   Fully Paid\n",
      "1   < 1 year           RENT     30000.0     Source Verified  Charged Off\n",
      "2  10+ years           RENT     12252.0        Not Verified   Fully Paid\n",
      "3  10+ years           RENT     49200.0     Source Verified   Fully Paid\n",
      "4     1 year           RENT     80000.0     Source Verified      Current\n",
      "  pymnt_plan         purpose                 title addr_state    dti\n",
      "0          n     credit_card              Computer         AZ  27.65\n",
      "1          n             car                  bike         GA   1.00\n",
      "2          n  small_business  real estate business         IL   8.72\n",
      "3          n           other              personel         CA  20.00\n",
      "4          n           other              Personal         OR  17.94\n",
      "   delinq_2yrs earliest_cr_line  inq_last_6mths  open_acc  pub_rec\n",
      "0          0.0         Jan-1985             1.0       3.0      0.0\n",
      "1          0.0         Apr-1999             5.0       3.0      0.0\n",
      "2          0.0         Nov-2001             2.0       2.0      0.0\n",
      "3          0.0         Feb-1996             1.0      10.0      0.0\n",
      "4          0.0         Jan-1996             0.0      15.0      0.0\n",
      "   revol_bal revol_util  total_acc initial_list_status last_credit_pull_d\n",
      "0    13648.0      83.7%        9.0                   f           Jun-2016\n",
      "1     1687.0       9.4%        4.0                   f           Sep-2013\n",
      "2     2956.0      98.5%       10.0                   f           Jun-2016\n",
      "3     5598.0        21%       37.0                   f           Apr-2016\n",
      "4    27783.0      53.9%       38.0                   f           Jun-2016\n",
      "   collections_12_mths_ex_med  ...  chargeoff_within_12_mths\n",
      "0                         0.0  ...                       0.0\n",
      "1                         0.0  ...                       0.0\n",
      "2                         0.0  ...                       0.0\n",
      "3                         0.0  ...                       0.0\n",
      "4                         0.0  ...                       0.0\n",
      "\n",
      "[5 rows x 5 columns]\n",
      "   delinq_amnt  pub_rec_bankruptcies  tax_liens\n",
      "0          0.0                   0.0        0.0\n",
      "1          0.0                   0.0        0.0\n",
      "2          0.0                   0.0        0.0\n",
      "3          0.0                   0.0        0.0\n",
      "4          0.0                   0.0        0.0\n"
     ]
    }
   ],
   "source": [
    "for i in range(0,33,5):\n",
    "  print(data.iloc[:,i:i+5].head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 187
    },
    "colab_type": "code",
    "id": "RpfocLF_ir3V",
    "outputId": "a4d7a278-4720-4c63-b699-0452c2afbe7c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Fully Paid                                             33136\n",
       "Charged Off                                             5634\n",
       "Does not meet the credit policy. Status:Fully Paid      1988\n",
       "Current                                                  961\n",
       "Does not meet the credit policy. Status:Charged Off      761\n",
       "Late (31-120 days)                                        24\n",
       "In Grace Period                                           20\n",
       "Late (16-30 days)                                          8\n",
       "Default                                                    3\n",
       "Name: loan_status, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['loan_status'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "SrGjxc0Bk_BR"
   },
   "outputs": [],
   "source": [
    "### WE ARE ONLY CONCERNED WITH FULLY PAID OR DEFAULT\n",
    "not_target = ['Current','Late (31-120 days)','In Grace Period','Late (16-30 days)','Default','Does not meet the credit policy. Status:Fully Paid','Does not meet the credit policy. Status:Charged Off']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 85
    },
    "colab_type": "code",
    "id": "SfgYbCpWjjXG",
    "outputId": "0a0ab4c3-6aec-42eb-9024-c931979af22a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(38773, 33)\n",
      "0.0    33136\n",
      "1.0     5634\n",
      "Name: loan_status, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "## NARROWING DOWN OUR TARGET CATEGORIES\n",
    "data = data[~data.loan_status.isin(not_target)]\n",
    "print(data.shape)\n",
    "mapping = {'Fully Paid':0,'Does not meet the credit policy. Status:Fully Paid':0,'Charged Off':1,'Does not meet the credit policy. Status:Charged Off':1}\n",
    "data['loan_status']= data['loan_status'].map(mapping)\n",
    "print(data['loan_status'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 578
    },
    "colab_type": "code",
    "id": "_y1JATtFpSJJ",
    "outputId": "4ea3ab62-356e-400c-faa3-e3b7b6fd4fe0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "multiple unique values loan_amnt 870\n",
      "multiple unique values term 2\n",
      "multiple unique values int_rate 371\n",
      "multiple unique values installment 15091\n",
      "multiple unique values grade 7\n",
      "multiple unique values emp_length 11\n",
      "multiple unique values home_ownership 5\n",
      "multiple unique values annual_inc 5234\n",
      "multiple unique values verification_status 3\n",
      "multiple unique values loan_status 2\n",
      "only one unique value pymnt_plan ['n']\n",
      "multiple unique values purpose 14\n",
      "multiple unique values title 19365\n",
      "multiple unique values addr_state 50\n",
      "multiple unique values dti 2856\n",
      "multiple unique values delinq_2yrs 11\n",
      "multiple unique values earliest_cr_line 524\n",
      "multiple unique values inq_last_6mths 9\n",
      "multiple unique values open_acc 40\n",
      "multiple unique values pub_rec 5\n",
      "multiple unique values revol_bal 21348\n",
      "multiple unique values revol_util 1088\n",
      "multiple unique values total_acc 82\n",
      "only one unique value initial_list_status ['f']\n",
      "multiple unique values last_credit_pull_d 107\n",
      "only one unique value collections_12_mths_ex_med [0.]\n",
      "only one unique value policy_code [1.]\n",
      "only one unique value application_type ['INDIVIDUAL']\n",
      "only one unique value acc_now_delinq [0.]\n",
      "only one unique value chargeoff_within_12_mths [0.]\n",
      "only one unique value delinq_amnt [0.]\n",
      "multiple unique values pub_rec_bankruptcies 3\n",
      "only one unique value tax_liens [0.]\n"
     ]
    }
   ],
   "source": [
    "###IDENTIFYING WHICH FEATURE COLUMNS HELP IN MAKING BETTER PREDICTIONS\n",
    "for column in data.columns:\n",
    "  uniq= data[column].dropna().unique()\n",
    "  if len(uniq)>=2:\n",
    "    print(f'multiple unique values {column} {len(uniq)}')\n",
    "  else:\n",
    "    data=data.drop(columns=column)\n",
    "    print(f'only one unique value {column} {uniq}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 119
    },
    "colab_type": "code",
    "id": "c52wOGjEtRxr",
    "outputId": "35764f5f-c64a-48b9-c3ca-470a6ac6ec35"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "emp_length              1036\n",
      "title                     11\n",
      "revol_util                50\n",
      "last_credit_pull_d         2\n",
      "pub_rec_bankruptcies     697\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "##DROPPING VALUES WITHOUT ANY TARGET VARIABLE INFORMATION\n",
    "data = data.dropna(subset=['loan_status'])\n",
    "print(data.isnull().sum()[data.isnull().sum()>0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 85
    },
    "colab_type": "code",
    "id": "EH7m6kHd0h9b",
    "outputId": "f25dea65-f925-4463-9e60-1c3e0c6a8368"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    36422\n",
       "1.0     1646\n",
       "2.0        5\n",
       "Name: pub_rec_bankruptcies, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['pub_rec_bankruptcies'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 425
    },
    "colab_type": "code",
    "id": "AtP1fmSE07ld",
    "outputId": "c2ca3310-675b-45ff-b8de-edbfc65fd533"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loan_amnt              0\n",
      "term                   0\n",
      "int_rate               0\n",
      "installment            0\n",
      "grade                  0\n",
      "emp_length             0\n",
      "home_ownership         0\n",
      "annual_inc             0\n",
      "verification_status    0\n",
      "loan_status            0\n",
      "purpose                0\n",
      "title                  0\n",
      "addr_state             0\n",
      "dti                    0\n",
      "delinq_2yrs            0\n",
      "earliest_cr_line       0\n",
      "inq_last_6mths         0\n",
      "open_acc               0\n",
      "pub_rec                0\n",
      "revol_bal              0\n",
      "revol_util             0\n",
      "total_acc              0\n",
      "last_credit_pull_d     0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "data = data.dropna(subset=['emp_length','title','revol_util','last_credit_pull_d'])\n",
    "data = data.drop(columns=['pub_rec_bankruptcies'], axis=1)\n",
    "print(data.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "id": "uxQXousd1z69",
    "outputId": "20b89636-870a-466a-8ad0-8d20f7c45f54"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "object     12\n",
      "float64    11\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(data.dtypes.value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 419
    },
    "colab_type": "code",
    "id": "A8hfDfUz2BSQ",
    "outputId": "6d7eb211-d37b-43af-99c3-f64bb7a4d40d"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>installment</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>total_acc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>162.87</td>\n",
       "      <td>24000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13648.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2500.0</td>\n",
       "      <td>59.83</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1687.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2400.0</td>\n",
       "      <td>84.33</td>\n",
       "      <td>12252.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2956.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>339.31</td>\n",
       "      <td>49200.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5598.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>156.46</td>\n",
       "      <td>36000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7963.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39781</th>\n",
       "      <td>2500.0</td>\n",
       "      <td>78.42</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7274.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39782</th>\n",
       "      <td>8500.0</td>\n",
       "      <td>275.38</td>\n",
       "      <td>18000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.40</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8847.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39783</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>156.84</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9698.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39784</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>155.38</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85607.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39785</th>\n",
       "      <td>7500.0</td>\n",
       "      <td>255.43</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.29</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4175.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37675 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       loan_amnt  installment  annual_inc  ...  pub_rec  revol_bal  total_acc\n",
       "0         5000.0       162.87     24000.0  ...      0.0    13648.0        9.0\n",
       "1         2500.0        59.83     30000.0  ...      0.0     1687.0        4.0\n",
       "2         2400.0        84.33     12252.0  ...      0.0     2956.0       10.0\n",
       "3        10000.0       339.31     49200.0  ...      0.0     5598.0       37.0\n",
       "5         5000.0       156.46     36000.0  ...      0.0     7963.0       12.0\n",
       "...          ...          ...         ...  ...      ...        ...        ...\n",
       "39781     2500.0        78.42    110000.0  ...      0.0     7274.0       40.0\n",
       "39782     8500.0       275.38     18000.0  ...      0.0     8847.0        9.0\n",
       "39783     5000.0       156.84    100000.0  ...      0.0     9698.0       20.0\n",
       "39784     5000.0       155.38    200000.0  ...      0.0    85607.0       26.0\n",
       "39785     7500.0       255.43     22000.0  ...      0.0     4175.0        8.0\n",
       "\n",
       "[37675 rows x 11 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## CONTINIOUS FEATURES\n",
    "float_df = data.select_dtypes(include=['float'])\n",
    "float_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 589
    },
    "colab_type": "code",
    "id": "2Y-SpJpz2eIq",
    "outputId": "05c572d7-6cec-4bbc-9e91-8810a5b04f5f"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>term</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>grade</th>\n",
       "      <th>emp_length</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>purpose</th>\n",
       "      <th>title</th>\n",
       "      <th>addr_state</th>\n",
       "      <th>earliest_cr_line</th>\n",
       "      <th>revol_util</th>\n",
       "      <th>last_credit_pull_d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36 months</td>\n",
       "      <td>10.65%</td>\n",
       "      <td>B</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>Verified</td>\n",
       "      <td>credit_card</td>\n",
       "      <td>Computer</td>\n",
       "      <td>AZ</td>\n",
       "      <td>Jan-1985</td>\n",
       "      <td>83.7%</td>\n",
       "      <td>Jun-2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60 months</td>\n",
       "      <td>15.27%</td>\n",
       "      <td>C</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>RENT</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>car</td>\n",
       "      <td>bike</td>\n",
       "      <td>GA</td>\n",
       "      <td>Apr-1999</td>\n",
       "      <td>9.4%</td>\n",
       "      <td>Sep-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36 months</td>\n",
       "      <td>15.96%</td>\n",
       "      <td>C</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>small_business</td>\n",
       "      <td>real estate business</td>\n",
       "      <td>IL</td>\n",
       "      <td>Nov-2001</td>\n",
       "      <td>98.5%</td>\n",
       "      <td>Jun-2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36 months</td>\n",
       "      <td>13.49%</td>\n",
       "      <td>C</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>other</td>\n",
       "      <td>personel</td>\n",
       "      <td>CA</td>\n",
       "      <td>Feb-1996</td>\n",
       "      <td>21%</td>\n",
       "      <td>Apr-2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>36 months</td>\n",
       "      <td>7.90%</td>\n",
       "      <td>A</td>\n",
       "      <td>3 years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>wedding</td>\n",
       "      <td>My wedding loan I promise to pay back</td>\n",
       "      <td>AZ</td>\n",
       "      <td>Nov-2004</td>\n",
       "      <td>28.3%</td>\n",
       "      <td>Jan-2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39781</th>\n",
       "      <td>36 months</td>\n",
       "      <td>8.07%</td>\n",
       "      <td>A</td>\n",
       "      <td>4 years</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>home_improvement</td>\n",
       "      <td>Home Improvement</td>\n",
       "      <td>CO</td>\n",
       "      <td>Nov-1990</td>\n",
       "      <td>13.1%</td>\n",
       "      <td>Jun-2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39782</th>\n",
       "      <td>36 months</td>\n",
       "      <td>10.28%</td>\n",
       "      <td>C</td>\n",
       "      <td>3 years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>credit_card</td>\n",
       "      <td>Retiring credit card debt</td>\n",
       "      <td>NC</td>\n",
       "      <td>Dec-1986</td>\n",
       "      <td>26.9%</td>\n",
       "      <td>Jul-2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39783</th>\n",
       "      <td>36 months</td>\n",
       "      <td>8.07%</td>\n",
       "      <td>A</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>debt_consolidation</td>\n",
       "      <td>MBA Loan Consolidation</td>\n",
       "      <td>MA</td>\n",
       "      <td>Oct-1998</td>\n",
       "      <td>19.4%</td>\n",
       "      <td>Jun-2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39784</th>\n",
       "      <td>36 months</td>\n",
       "      <td>7.43%</td>\n",
       "      <td>A</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>other</td>\n",
       "      <td>JAL Loan</td>\n",
       "      <td>MD</td>\n",
       "      <td>Nov-1988</td>\n",
       "      <td>0.7%</td>\n",
       "      <td>Jun-2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39785</th>\n",
       "      <td>36 months</td>\n",
       "      <td>13.75%</td>\n",
       "      <td>E</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>OWN</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>debt_consolidation</td>\n",
       "      <td>Consolidation Loan</td>\n",
       "      <td>MA</td>\n",
       "      <td>Oct-2003</td>\n",
       "      <td>51.5%</td>\n",
       "      <td>Jun-2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37675 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             term int_rate grade  ... earliest_cr_line revol_util last_credit_pull_d\n",
       "0       36 months   10.65%     B  ...         Jan-1985      83.7%           Jun-2016\n",
       "1       60 months   15.27%     C  ...         Apr-1999       9.4%           Sep-2013\n",
       "2       36 months   15.96%     C  ...         Nov-2001      98.5%           Jun-2016\n",
       "3       36 months   13.49%     C  ...         Feb-1996        21%           Apr-2016\n",
       "5       36 months    7.90%     A  ...         Nov-2004      28.3%           Jan-2016\n",
       "...           ...      ...   ...  ...              ...        ...                ...\n",
       "39781   36 months    8.07%     A  ...         Nov-1990      13.1%           Jun-2010\n",
       "39782   36 months   10.28%     C  ...         Dec-1986      26.9%           Jul-2010\n",
       "39783   36 months    8.07%     A  ...         Oct-1998      19.4%           Jun-2007\n",
       "39784   36 months    7.43%     A  ...         Nov-1988       0.7%           Jun-2007\n",
       "39785   36 months   13.75%     E  ...         Oct-2003      51.5%           Jun-2010\n",
       "\n",
       "[37675 rows x 12 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##CATEGORICAL FEATURES\n",
    "object_df = data.select_dtypes(include=['object'])\n",
    "object_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "tCkvQAlr4rBa",
    "outputId": "685d6f60-3ff8-4f9f-86ef-bd654d80fb09"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RENT        18112\n",
      "MORTGAGE    16686\n",
      "OWN          2778\n",
      "OTHER          96\n",
      "NONE            3\n",
      "Name: home_ownership, dtype: int64\n",
      "Not Verified       16281\n",
      "Verified           11856\n",
      "Source Verified     9538\n",
      "Name: verification_status, dtype: int64\n",
      "10+ years    8545\n",
      "< 1 year     4513\n",
      "2 years      4303\n",
      "3 years      4022\n",
      "4 years      3353\n",
      "5 years      3202\n",
      "1 year       3176\n",
      "6 years      2177\n",
      "7 years      1714\n",
      "8 years      1442\n",
      "9 years      1228\n",
      "Name: emp_length, dtype: int64\n",
      " 36 months    28234\n",
      " 60 months     9441\n",
      "Name: term, dtype: int64\n",
      "CA    6776\n",
      "NY    3614\n",
      "FL    2704\n",
      "TX    2613\n",
      "NJ    1776\n",
      "IL    1447\n",
      "PA    1442\n",
      "VA    1347\n",
      "GA    1323\n",
      "MA    1272\n",
      "OH    1149\n",
      "MD    1008\n",
      "AZ     807\n",
      "WA     788\n",
      "CO     748\n",
      "NC     729\n",
      "CT     711\n",
      "MI     678\n",
      "MO     648\n",
      "MN     581\n",
      "NV     466\n",
      "SC     454\n",
      "WI     427\n",
      "OR     422\n",
      "LA     420\n",
      "AL     420\n",
      "KY     311\n",
      "OK     285\n",
      "UT     249\n",
      "KS     249\n",
      "AR     229\n",
      "DC     209\n",
      "RI     194\n",
      "NM     180\n",
      "WV     164\n",
      "HI     162\n",
      "NH     157\n",
      "DE     110\n",
      "MT      77\n",
      "AK      76\n",
      "WY      76\n",
      "SD      60\n",
      "VT      53\n",
      "MS      19\n",
      "TN      17\n",
      "IN       9\n",
      "ID       6\n",
      "IA       5\n",
      "NE       5\n",
      "ME       3\n",
      "Name: addr_state, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "cols = ['home_ownership', 'verification_status', 'emp_length', 'term', 'addr_state']\n",
    "for col in cols:\n",
    "  print(data[col].value_counts())\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "TrXF-FaV9f9Q"
   },
   "outputs": [],
   "source": [
    "data = data.drop(columns=[\"last_credit_pull_d\", \"earliest_cr_line\", \"title\",'grade', \"addr_state\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "wmlDnEB_-djw"
   },
   "outputs": [],
   "source": [
    "mapping_dict = {\n",
    "        \"10+ years\": \"experienced\",\n",
    "        \"9 years\": \"experienced\",\n",
    "        \"8 years\": \"experienced\",\n",
    "        \"7 years\": \"experienced\",\n",
    "        \"6 years\": \"intermediate\",\n",
    "        \"5 years\": \"intermediate\",\n",
    "        \"4 years\": \"intermediate\",\n",
    "        \"3 years\": \"beginner\",\n",
    "        \"2 years\": \"beginner\",\n",
    "        \"1 year\": \"beginner\",\n",
    "        \"< 1 year\": \"beginner\",\n",
    "        \"n/a\": \"beginner\"\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 309
    },
    "colab_type": "code",
    "id": "Rtb1ceRD_Dw-",
    "outputId": "1f440abe-15b4-4360-a083-4f333c87746a"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>term</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>emp_length</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>purpose</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>revol_util</th>\n",
       "      <th>total_acc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>36 months</td>\n",
       "      <td>10.65</td>\n",
       "      <td>162.87</td>\n",
       "      <td>experienced</td>\n",
       "      <td>RENT</td>\n",
       "      <td>24000.0</td>\n",
       "      <td>Verified</td>\n",
       "      <td>0.0</td>\n",
       "      <td>credit_card</td>\n",
       "      <td>27.65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13648.0</td>\n",
       "      <td>83.7</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2500.0</td>\n",
       "      <td>60 months</td>\n",
       "      <td>15.27</td>\n",
       "      <td>59.83</td>\n",
       "      <td>beginner</td>\n",
       "      <td>RENT</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>1.0</td>\n",
       "      <td>car</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1687.0</td>\n",
       "      <td>9.4</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2400.0</td>\n",
       "      <td>36 months</td>\n",
       "      <td>15.96</td>\n",
       "      <td>84.33</td>\n",
       "      <td>experienced</td>\n",
       "      <td>RENT</td>\n",
       "      <td>12252.0</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>0.0</td>\n",
       "      <td>small_business</td>\n",
       "      <td>8.72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2956.0</td>\n",
       "      <td>98.5</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>36 months</td>\n",
       "      <td>13.49</td>\n",
       "      <td>339.31</td>\n",
       "      <td>experienced</td>\n",
       "      <td>RENT</td>\n",
       "      <td>49200.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>0.0</td>\n",
       "      <td>other</td>\n",
       "      <td>20.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5598.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>36 months</td>\n",
       "      <td>7.90</td>\n",
       "      <td>156.46</td>\n",
       "      <td>beginner</td>\n",
       "      <td>RENT</td>\n",
       "      <td>36000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>0.0</td>\n",
       "      <td>wedding</td>\n",
       "      <td>11.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7963.0</td>\n",
       "      <td>28.3</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt        term  int_rate  ...  revol_bal revol_util total_acc\n",
       "0     5000.0   36 months     10.65  ...    13648.0       83.7       9.0\n",
       "1     2500.0   60 months     15.27  ...     1687.0        9.4       4.0\n",
       "2     2400.0   36 months     15.96  ...     2956.0       98.5      10.0\n",
       "3    10000.0   36 months     13.49  ...     5598.0       21.0      37.0\n",
       "5     5000.0   36 months      7.90  ...     7963.0       28.3      12.0\n",
       "\n",
       "[5 rows x 18 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['emp_length']= data['emp_length'].map(mapping_dict)\n",
    "data['int_rate']= data['int_rate'].str.rstrip('%').astype(\"float\")\n",
    "data['revol_util']= data['revol_util'].str.rstrip('%').astype(\"float\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 272
    },
    "colab_type": "code",
    "id": "KZ_OgtVoHAPx",
    "outputId": "84adcfff-993c-411b-f145-4e649f0fbc30"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "debt_consolidation    17751\n",
       "credit_card            4911\n",
       "other                  3711\n",
       "home_improvement       2808\n",
       "major_purchase         2083\n",
       "small_business         1719\n",
       "car                    1459\n",
       "wedding                 916\n",
       "medical                 655\n",
       "moving                  552\n",
       "house                   356\n",
       "vacation                348\n",
       "educational             312\n",
       "renewable_energy         94\n",
       "Name: purpose, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['purpose'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 473
    },
    "colab_type": "code",
    "id": "74maBfmAH2ZW",
    "outputId": "53cf4b4b-d2b2-46bc-c105-ba8dbc1ceefc"
   },
   "outputs": [
    {
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       "      <th>installment</th>\n",
       "      <th>annual_inc</th>\n",
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       "      <th>dti</th>\n",
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       "      <th>purpose_small_business</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.90</td>\n",
       "      <td>156.46</td>\n",
       "      <td>36000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7963.0</td>\n",
       "      <td>28.3</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39781</th>\n",
       "      <td>2500.0</td>\n",
       "      <td>8.07</td>\n",
       "      <td>78.42</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7274.0</td>\n",
       "      <td>13.1</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39782</th>\n",
       "      <td>8500.0</td>\n",
       "      <td>10.28</td>\n",
       "      <td>275.38</td>\n",
       "      <td>18000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.40</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8847.0</td>\n",
       "      <td>26.9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39783</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>8.07</td>\n",
       "      <td>156.84</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9698.0</td>\n",
       "      <td>19.4</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39784</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.43</td>\n",
       "      <td>155.38</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85607.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39785</th>\n",
       "      <td>7500.0</td>\n",
       "      <td>13.75</td>\n",
       "      <td>255.43</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.29</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4175.0</td>\n",
       "      <td>51.5</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37675 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       loan_amnt  int_rate  ...  emp_length_experienced  emp_length_intermediate\n",
       "0         5000.0     10.65  ...                       1                        0\n",
       "1         2500.0     15.27  ...                       0                        0\n",
       "2         2400.0     15.96  ...                       1                        0\n",
       "3        10000.0     13.49  ...                       1                        0\n",
       "5         5000.0      7.90  ...                       0                        0\n",
       "...          ...       ...  ...                     ...                      ...\n",
       "39781     2500.0      8.07  ...                       0                        1\n",
       "39782     8500.0     10.28  ...                       0                        0\n",
       "39783     5000.0      8.07  ...                       0                        0\n",
       "39784     5000.0      7.43  ...                       0                        0\n",
       "39785     7500.0     13.75  ...                       0                        0\n",
       "\n",
       "[37675 rows x 40 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##ONE_HOT ENCODING FOR DUMMY VARIABLE\n",
    "cat_cols= [\"home_ownership\", \"verification_status\", \"purpose\", \"term\", 'emp_length']\n",
    "dummy_df = pd.get_dummies(data[cat_cols])\n",
    "data = pd.concat([data, dummy_df], axis=1)\n",
    "data = data.drop(cat_cols, axis=1)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 782
    },
    "colab_type": "code",
    "id": "uPM4fXwGMbqu",
    "outputId": "af74d329-cdbd-456c-b006-c5d27121bc8f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 37675 entries, 0 to 39785\n",
      "Data columns (total 40 columns):\n",
      "loan_amnt                              37675 non-null float64\n",
      "int_rate                               37675 non-null float64\n",
      "installment                            37675 non-null float64\n",
      "annual_inc                             37675 non-null float64\n",
      "loan_status                            37675 non-null float64\n",
      "dti                                    37675 non-null float64\n",
      "delinq_2yrs                            37675 non-null float64\n",
      "inq_last_6mths                         37675 non-null float64\n",
      "open_acc                               37675 non-null float64\n",
      "pub_rec                                37675 non-null float64\n",
      "revol_bal                              37675 non-null float64\n",
      "revol_util                             37675 non-null float64\n",
      "total_acc                              37675 non-null float64\n",
      "home_ownership_MORTGAGE                37675 non-null uint8\n",
      "home_ownership_NONE                    37675 non-null uint8\n",
      "home_ownership_OTHER                   37675 non-null uint8\n",
      "home_ownership_OWN                     37675 non-null uint8\n",
      "home_ownership_RENT                    37675 non-null uint8\n",
      "verification_status_Not Verified       37675 non-null uint8\n",
      "verification_status_Source Verified    37675 non-null uint8\n",
      "verification_status_Verified           37675 non-null uint8\n",
      "purpose_car                            37675 non-null uint8\n",
      "purpose_credit_card                    37675 non-null uint8\n",
      "purpose_debt_consolidation             37675 non-null uint8\n",
      "purpose_educational                    37675 non-null uint8\n",
      "purpose_home_improvement               37675 non-null uint8\n",
      "purpose_house                          37675 non-null uint8\n",
      "purpose_major_purchase                 37675 non-null uint8\n",
      "purpose_medical                        37675 non-null uint8\n",
      "purpose_moving                         37675 non-null uint8\n",
      "purpose_other                          37675 non-null uint8\n",
      "purpose_renewable_energy               37675 non-null uint8\n",
      "purpose_small_business                 37675 non-null uint8\n",
      "purpose_vacation                       37675 non-null uint8\n",
      "purpose_wedding                        37675 non-null uint8\n",
      "term_ 36 months                        37675 non-null uint8\n",
      "term_ 60 months                        37675 non-null uint8\n",
      "emp_length_beginner                    37675 non-null uint8\n",
      "emp_length_experienced                 37675 non-null uint8\n",
      "emp_length_intermediate                37675 non-null uint8\n",
      "dtypes: float64(13), uint8(27)\n",
      "memory usage: 5.0 MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "USqhmeaNPuhW"
   },
   "source": [
    "False positive rate is the number of false positives divided by the number of false positives plus the number of true negatives. This divides all the cases where we thought a loan would be paid off but it wasn't by all the loans that weren't paid off:\n",
    "\n",
    "fpr = fp / (fp + tn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "8hpjdna7Pwld"
   },
   "source": [
    "True positive rate is the number of true positives divided by the number of true positives plus the number of false negatives. This divides all the cases where we thought a loan would be paid off and it was by all the loans that were paid off:\n",
    "\n",
    "tpr = tp / (tp + fn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "UMcQmS_ghA36"
   },
   "source": [
    "## Precision = ((True Positive)/(True Positive + False Positive))\n",
    "## Recall = ((True Positive)/(True Positive + False Negative))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "QYcP4AN9e-BJ"
   },
   "source": [
    "# SETTING UP MODEL EVALUATION CRITERIA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "V6QIV9AlYjUk"
   },
   "outputs": [],
   "source": [
    "def model_performance(target, predictions):\n",
    "  fig, ((ax1, ax2, ax3)) = plt.subplots(1, 3, sharex=False, sharey=False,figsize=[16,4])\n",
    "  ax1.bar(x=target.value_counts().index.astype(str), height=target.value_counts().to_list(), data=target, color=['b','r'])\n",
    "\n",
    "  metric = metrics.confusion_matrix(target,predictions)\n",
    "  confusion_dataframe = pd.DataFrame(data=metric, index=['Actual_Positive','Actual_Negative'], columns=['Guessed_Positive', 'Guessed_Negative'])\n",
    "  sns.heatmap(confusion_dataframe, annot=True, fmt=\"d\", cmap=\"YlGnBu\", ax = ax2)\n",
    "\n",
    "  fpr, tpr, _ = (metrics.roc_curve(target,predictions))\n",
    "  plt.plot(fpr, tpr)\n",
    "  \n",
    "\n",
    "  fpr, tpr, _ = (metrics.roc_curve(target,predictions))\n",
    "  ax3.plot(fpr, tpr)\n",
    "  roc_auc = auc(fpr, tpr)\n",
    "  ax3.plot([0, 1], [0, 1], 'k--', label='AUC = %0.3f'% roc_auc)\n",
    "  ax3.legend(loc='lower right')\n",
    "  ax3.plot([0,1],[0,1],'r--')\n",
    "  ax3.set_xlim([-0.1,1.0])\n",
    "  ax3.set_ylim([-0.1,1.01])\n",
    "  ax3.set_ylabel('True Positive Rate')\n",
    "  ax3.set_xlabel('False Positive Rate')\n",
    "  plt.tight_layout()\n",
    "  print(f'Area Under the Curve: {round(roc_auc,2)}')\n",
    "\n",
    "\n",
    "    \n",
    "  plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "6rrAZyDcP-lB"
   },
   "outputs": [],
   "source": [
    "features = data.drop(columns=['loan_status'],axis=1)\n",
    "target = data['loan_status']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "7Tv1LpdRa_HF"
   },
   "source": [
    "# LOGISTIC REGRESSION WITH VANILA, BALACNED WEIGHT AND CUSTOM PENALTY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "eCguI3yjRpwZ"
   },
   "outputs": [],
   "source": [
    "lr = LogisticRegression()\n",
    "#X1_train, X1_test, y1_train, y1_test = train_test_split(features, target, test_size=0.33, random_state=42)\n",
    "#lr1 = LogisticRegression()\n",
    "#lr1.fit(X1_train,y1_train)\n",
    "#predictions1 = lr1.predict(X1_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "3id5ZI86SkcL"
   },
   "outputs": [],
   "source": [
    "predictions = cross_val_predict(lr, features, target, cv=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 314
    },
    "colab_type": "code",
    "id": "ALzKdaXMnRmb",
    "outputId": "60771823-95e3-4fc5-b5f8-36a735ca0078"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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RERERSX7K28Sdu48GRu/RdlfU/lzg1OKOS0RKF8/LI+ui7pzy+ns0AEaenkmPT6ao1s5+\n0E9MRERERJKfWexbobeyOmY23szmmtkcM7spaL/HzJaa2axg6xJ1TX8zW2Bm882sY1R7p6BtgZnd\nEdVe38ymBO1vBNOgRESSyvp1q5n2SE+O+e97rM0wZg8aSM+J05Tc2U/6qYmIiIhI8otjggfIAW51\n98ZAS+A6M2scnHvC3ZsG2+jIU1tjIjVqjiVSdPgZM0s3s3RgINAZaAz0jbrPQ8G9jgbWESlYLCKS\nND5+5G5W3XcSJ275jMV3XEKtpSs4+aprww6rVNMULRERERFJfnH8WtPdlwPLg/2NZjYPqLWPS3oA\nw9x9O7DIzBYAzYNzC9x9IYCZDQN6BPdrC1wY9HkZuAd4Nn6vQkQkHDu2bWXU6U3pnP0/vqhZlrwx\nY+nYrHXYYSUFjeARERERkeRXhBE8ZtbPzLKjtn4F39bqAScCU4Km683sKzMbYmaHBG21gB+jLlsS\ntBXUXh34OShkHN0uIlKqzfngXbJrVKZ39v+YdXBZGoz8kEZK7sSNRvCIiIgUg3LlyvDhf++ibNky\nZGSk8/boKTzw+Ju8+OR1NGtyFDtzcsme9R3X93+enJxcLuh5Krdc0x0z2LRpGzf+9QVmz/uhwPsA\nnHnKsfzjr7+nbNkMZs5exB9ve47c3LyQX7nsj9zcXM455xYOO6wazz13NxdeeDubN28FYM2a9TRp\n0pBnnvlbyFGWMkUosuzug4BBhd7SrCLwFnCzu28ws2eB+wEPHh8DrtifcEVEkonn5THqhoto/uzr\nHO0wstWJdJ84lbQMpSTiST9NERGRYrB9+046XfAAm7dsJyMjnY/fuocPxs9i2MjPufymgQC8/PQN\nXH5BGwa/+iHf/7iSDn3u4+f1m+nQ+gQGPngVZ/T4vwLvM23Wdzz/+DV07vsACxat4P9uOZeLzj2D\nl9/4JNwXLvtl6NB3adCgNps2bQHgtdce+uXcDTf8nXbtWoYVWqnlcV7+3MzKEEnu/MfdRwC4+09R\n5wcDo4LDpUCdqMtrB20U0L4GqGpmGcEonuj+IiKlyvp1q1kw5CpO2v4By8qm8/3jj9Hz2pvCDisp\naYqWiIhIMdm8ZTsAZTLSychIx90ZO37WL+ezZy2g1uHVAJg8/Vt+Xr8ZgKkzf20v6D7VD6nIjp05\nLFi0AoCPP5tNz87NkdJnxYrVfPLJNM49t8Ne5zZt2sLkyV9x1llK8BRZfFfRMuAFYJ67Px7VfnhU\nt17A18F+FnCBmZUzs/pAQ2AqMA1oGKyYVZZIIeYsd3dgPHBucP2lwDsH9PpFRELwyWP3Me13tTj+\n549ZfNoNNNm0jRZK7iSMRvCIiEjCmdlpQEN3f9HMagIV3X1R2HEVt7Q044v3/k6Der/huaEfMG3W\nd7+cy8hIp2/v07nt3pf3uu6y81vvlggq6D4Z6Wk0a3IUM75aSK8uLah9RPXEvyiJu7//fTC33Xb5\nL1Oyon344WRatTqBihUPCiGyUi49riN4TgUuBmab2a5fzjuJrILVlMgUre+BqwHcfY6ZDQfmElmB\n6zp3zwUws+uBsUA6MMTd5wT3ux0YZmYPADOJJJREREqFndu38e4ZTek0dT5bgSmHD+D0y/4cdlhJ\nr9AEj5nVAYYChxF5sxrk7k+a2T3AVcCqoOudUUtB9ieylGMucKO7jw3aOwFPEnkDe97dHwza6wPD\niBSUmw5c7O474vUiRUQkPGZ2N5AJHAO8CJQBXiXyASml5OU5LTv3p0rlg3hj0C00blSbuf9bAsCT\nA67g86nf8PnU+btdc0arxlx6fhvanXNPofe55PqnefiuiylXNoMPJ85W/Z1SaPz4qVSrVoXjjjua\nKVNm73V+1KgJnHfe3iN7JAaxLX8eE3f/jPyr+ozexzUDgAH5tI/O77pgZS0NwxORUmfeR2NY07M7\nvTftZMpBZTl07DhOP+2MsMNKCbFM0coBbnX3xkBL4Dozaxyce8LdmwbbruROYyLDS48FOgHPmFm6\nmaUDA4HOQGMi33Dsus9Dwb2OBtYRSQ6JiEhy6AV0BzYDuPsyoNK+LohewSZn04JiCLF4rd+whQmT\n5tKh9QkA3HnzOdSsVom/3PfKbv2O+21dnn24H+f94VHW/ryp0PtMmfEtZ517L6d3/z8+mzLvl+la\nUnrMmDGPjz+eStu2V3LLLQ8zefJX/PnPjwGwdu16Zs/+ltatTw45ylLKirCJiEiReV4eU9/+Fzmd\nu9B8005GNj+Bk9dvpr6SO8Wm0ASPuy939xnB/kZgHvteprEHMMzdtwfD7xcQ+fahObDA3RcGo3OG\nAT2COcxtgTeD618Geu7vCxIRkRJnR1BPwgHM7ODCLnD3Qe6e6e6ZGRWPTniAxaFGtUpUqRyZVlO+\nXBnanX48879bxmUXtKH9GU245PqnifyYIuocUZ1hg/7ElTcP3C1RU9B9AGpWrwxA2bIZ3Hptdwa/\n+mFxvTyJk1tvvZSJE1/i449f4PHH/0LLlk149NFbARg79gtatz6ZcuXKhhxlKZVmsW8iIlIkq5cs\nZso/etL8y7+yrHN9pj/5KD2nzNIqWcWsSD9tM6sHnAhMITK0/nozuwTIJjLKZx2R5M/kqMuW8GtC\n6Mc92lsQmZb1c7BCwJ79RUSk9BtuZs8RWRHmKiJLBg8OOaZi95tDD2Hw49eQnp5GWprx1qjJvP/R\nTDYufJUflq7mk5H3AfDOmGn848kR9L+pN9UOqcg/H4issJyTm8dp3f5a4H0A/nR1Nzq3a0ZamjH4\n1Q+Z8MWcAuOR0mf06IlcddW5hXeU/ClxIyKSEBP/OYAat/0fWw9LY9L9t3LW3waQrsROKCz628J9\ndjSrCEwABrj7CDM7DFhN5BvZ+4HD3f0KM/sXMNndXw2uewF4P7hNJ3f/Q9B+MZEEzz1B/6OD9jrA\n++5+XD4x9AP6AdStW/ekxYsXF/0F671dAjH+X1+kRDOz6e6eGXYchTGz9kAHIpMfxrr7uFivrVC3\nr35bU9zWH+4NOwQpERod0F9xR/3hvzH/W7Lw+fP0F2NIMjMzPTs7O+wwRCQGO7dvI6tNMzpNmsd2\nYNIl59P15WFhh5UU9vdv/JjSamZWBngL+I+7jwBw95+izg8GRgWHS4E6UZfXDtoooH0NkW91M4JR\nPNH9d+Pug4BBEPnHP5bYRUQkXGZ2C/BGUZI6IiJxpxE8IiJx880nY1nV/WzO2biTaRXKUG30+3Rt\n3S7ssFJeoTV4gho5LwDz3P3xqPbDo7r1Ar4O9rOAC8ysXLA6VkNgKjANaGhm9c2sLJFCzFlBXYbx\nwK4xx5cC7xzYyxIRkRKkEvCBmX1qZtcHI0BFRIqXWeybiIgUKDvrWXYM7EPTjTt556TjOGnDFhoo\nuVMixLKK1qnAxUBbM5sVbF2Ah81stpl9BbQB/gTg7nOA4cBcYAxwnbvnBqNzrgfGEinUPDzoC3A7\ncIuZLSBSk+eF+L1EEREJk7vf6+7HAtcBhwMTzEzVf0WkeKnIsojIAVmz7EdGtmlE5ow7KNP0WJZO\nGEuP7NkqpFyCFPpfwt0/I/8FI0fv45oBwIB82kfnd527LySyypaIiCSvlcAKIlNzDw05FhFJNbF8\nrSkiIvn69OkHqXrrnfTc6bzToDNdnx1JRhmt6ljSKNUmIiIJZWbXAn2AmsB/gavcfW64UYlIyklX\nhkdEpKh2bt9G1lnN6fDZbHKA9y46jx7PDw87LCmAEjwiIpJodYCb3X1W2IGISOpy1dYRESmSZYu+\nYW7zEzln9Tayy2dQ5d3RdD2rfdhhyT4owSMiIglhZpXdfQPwSHBcLfq8u68NJTARSU0awCMiErPs\nrH9zzPR7yDjKeKdOY7pNnkl6WU3JKumU4BERkUR5DegGTAec3eu5OXBUGEGJSIpS8WQRkUKtXbGU\nz085gSoHrWdJ30wavfESR9Q7JuywJEZK8IiISEK4e7fgsX7YsYiIaPlzEZF9++zZR6l88184e4cz\n9vDqNPzLBBVSLmU0WFVERBLKzD6KpU1EJKG0TLqISL5ydu7grdZNaXLtbdTd4Yw6vxcdl61WcqcU\n0ggeERFJCDMrDxwE1DCzQ/h1ilZloFZogYlIalLeRkRkL8u+n883/c/mnAnfMqNcBhXfyaJbx85h\nhyX7SQkeERFJlKuBm4EjgBlR7RuAf4USkYikLNfInH0ys4PcfUvYcYhI8fn4ib9y8s8vcHIjeOfS\nXnQbNEyFlEs5JXhERCQh3P1J4Ekzu8Hdnw47HhFJcUrw5MvMTgGeByoCdc3sBOBqd7823MhEJFHW\n/bSMT09tSsfvVjHh7Poc9+RoetT/bdhhSRwowSMiIglhZm3d/WNgqZn13vO8u48IISwRSVUqslyQ\nJ4COQBaAu39pZmeEG5KIJMrng57g4BtupfsO58MaVch86iOq1dN6GMlCCR4REUmUM4GPgbPzOeeA\nEjwiUny0tEiB3P1H2z0BlhtWLCKSGDk7d/BO51ac9VFk1vyoc8+m23+zQo5K4k0JHhERSQh3vzt4\nvDzsWERESFeGpwA/BtO03MzKADcB80KOSUTiaNn381n/n8uovvhLFpbLoPyIEXTrkt/3b1La6Z1O\nREQSysxuMrPKFvG8mc0wsw5hxyUiKUbLpBfkj8B1RFY3XAo0BVR/RyRJjLrxUhZdfhJ1dizioIf+\nyfE/b+R3Su4kLY3gERGRRLvC3Z80s45AdeBi4BXgg3DDEpFU4qrBU5Bj3P330Q1mdirweUjxiEgc\n/LxqBRNOPYGu365kfhlj/fNTad6gcdhhSYJpBI+IiCTark9VXYCh7j4nqk1EpHikFWFLLfmtcqiV\nD0VKsc+HPMXCOrXo8e1KPq1Wid/MnU8tJXdSgkbwiIhIok03sw+A+kB/M6sE5IUck4ikGo3g2Y2Z\ntQJOAWqa2S1RpyoD6eFEJSIHIjcnhw/uupRW/3iNdGBUj850HTEKS0u9zHWq0n9pERFJtCuBO4CT\n3X0LUBZQ4WURKV6qwbOnskBFIl/4VoraNgDnxnIDM+tkZvPNbIGZ3VFAnz5mNtfM5pjZa3GKXUT2\nsGzRPP730Bl0yshiYoMa/PjO23QbOVrJnRSjETwiIpJQ7p5nZrWBC4NleCe4+7shhyUiqSZ1Ejcx\ncfcJwAQze8ndFxf1ejNLBwYC7YElwDQzy3L3uVF9GgL9gVPdfZ2ZHRqn8EUkyqg/Xc7R/3qJ3POq\nMv2Ch+l+3zVhhyQhUYJHREQSysweBE4G/hM03Whmrdz9zhDDEpFUo/xOQbaY2SPAsUD5XY3u3raQ\n65oDC9x9IYCZDQN6AHOj+lwFDHT3dcE9V8YzcJFUt371T3xy2gl0mf8TKw0WNrmV07sruZPKNF5L\nREQSrQvQ3t2HuPsQoBPQLeSYRCTFeJrFvBXGzOqY2fioqUc3Be3VzGycmX0bPB4StJuZPRVMZfrK\nzJpF3evSoP+3ZnZpVPtJZjY7uOYps4QVEfoP8A2ROmn3At8D02K4rhbwY9TxkqAtWiOgkZl9bmaT\nzazTgYcrIgCTXn6GBXWOoMf8n/j8kIqU++YbTr/jb2GHJSFTgkdERIpD1aj9KqFFISKpyyz2rXA5\nwK3u3hhoCVxnZo2J1Bv7yN0bAh8FxwCdgYbB1g94NhKSVQPuBloQGRFz966kUNDnqqjrEpUcqe7u\nLwA73X2Cu18BFDZ6J1YZRGJvDfQFBptZ1T07mVk/M8s2s+xVq1bF6alFklNuTg6TXrydbXfeyDHb\n8ni3WwfOXL2eGo2OCTs0KQGU4BERkUT7BzDTzF4ys5eB6cCAkGMSkVSTbrFvhXD35e4+I9jfCMwj\nMnqlB/By0O1loGew3wMY6hGTgapmdjjQERjn7muDaUzjgE7BucruPtndHRgada942xk8LjezrmZ2\nIlAthuuWAnWijmsHbdGWAFnuvtPdFwH/I5Lw2Y27D3L3THfPrFmzZtFfgUiKWDRjMp/9oQmtFv+b\ncn/sxOK33+Tsd8eqkLL8QjV4REQk0cYBE4DM4Ph2d18RYjwikoKK8vnHzPoRGWmzyyB3H1RA33rA\nicAU4DB3Xx6cWgEcFuwXNJ1pX+1L8mlPhAfMrApwK/A0kWXSb47humlAQzOrTySxcwFw4R59RhIZ\nufOimdUgMmVrYbwCF0klo//8B377xAscCUx+7QlanXejEjuyFyV4REQkIczsbGAIkakMucD57v55\nuFGJSKoqSgWbIJmTb0Jn9+FyvykAACAASURBVHtaReAt4GZ33xBdJsfd3cy86JEWL3cfFeyuB9oA\nmNmpMVyXY2bXA2OBdGCIu88xs/uAbHfPCs51MLO5RN4HbnP3NYl4HSLJasPaVXx8+gl0mbuc1Qbz\n+/+FNufHkoOVVKQEj4iIJMoA4HR3/8bMWgAPA2eGHJOIpKh4lyg2szJEkjv/cfcRQfNPZna4uy8P\nplntWjWqoOlMS4nUp4lu/yRor51P/3jGnw70ITIyaIy7f21m3YA7gQpERiXtk7uPBkbv0XZX1L4D\ntwSbiBTRzFHDyOnze3puzWNi1YP57RdTafO7xmGHJSWYxnSJiEii5Lj7NwDuPgWoFHI8IpLCzCzm\nLYZ7GfACMM/dH486lQXsWgnrUuCdqPZLgtW0WgLrg6lcu0a4HBIUV+4AjA3ObTCzlsFzXRJ1r3h5\nAfgDUB14ysxeBR4FHnb3QpM7IpI4uTk5THrpDhpPupo8g3c7t+P0NRs4VMkdKUShI3jMrA6Rwm6H\nAU5kDvKTQdX/N4B6RJZT7OPu64I3oSeJLIu7BbhsVxG6YOnHXWu3PeDuLwftJwEvEfm2YDRwU5Dx\nFxGR0utQM7uloOM9PhSJiCRUnEfwnApcDMw2s1lB253Ag8BwM7sSWExkhAxE/r7tAiwg8vfx5QDu\nvtbM7ufXZcnvc/e1wf61/Pr38fvBFk+ZQBN3zzOz8kRqBjXQFCqRcC36cirfdG1L5tnO10d34Jgf\nnqNF9UPDDktKiVimaO1aBnKGmVUCppvZOOAyIstAPmhmdxBZBvJ2dl8GsgWRJR5bRC0DmUkkUTTd\nzLKCFQN2LQM5hcgbYCfi/yYmIiLFazC7j9rZ81hEpNjEM8Hj7p8BBd2xXT79HbiugHsNIVKvbM/2\nbOC4AwizMDvcPS94rm1mtlDJHZFwjb79jzR67Dk658LbC1rRc+BbKqQsRVJogicYIro82N9oZtHL\nQLYOur1MZL7w7UQtAwlMNrNdy0C2JlgGEiBIEnUys08IloEM2nctA6kEj4hIKebu98bSz8z6u/s/\nEh2PiKQ202ekPf3WzL4K9g1oEBwbkZxUk/BCE0ktG9et5qMzmtL566WsMxj/lz/R6yENdJaiK1KR\n5bCXgYxesrJu3bpFCV1EREqu8wAleEQkoeJdZDkJ/C7sAEQE/jfjExae15WeC7fwaeWDaPj5ZNoc\nd3zYYUkpFXOCpyQsAxm9ZGVmZqZq9IiIJAd97BKRhEvTvzS7cffFYccgkspyc3L4fNBfaPXTS3iX\n6ry76FS6ZY3RlCw5IDEleEr7MpAiIlKiKWEvIgmnz0wiUlJ8Pzub/7U/kyPWbmHmvV055r6XOOaQ\nGmGHJUmg0Le6JFkGUkRESi59ry4iCRfPZdJFRPbXmL9ez84TT6bDT1v4oU5tmlzzKlWU3JE4iWUE\nTzIsAykiIiXXf8MOQESSn4osF8zMKgB13X1+2LGIJKtN69cy7owT6PzVEjYYfHTLDXR57Kmww5Ik\nE8sqWsmwDKSIiBQzM3uafUy/cvcbg8e/F1tQIpKyNDAnf2Z2NvAoUBaob2ZNiXwR2z3cyESSx/9m\nTCDtjStpMmcJ0ytVoMFnk2jX5ISww5IkVKRVtERERIogO+wARER2UYKnQPcAzYnUxsTdZ5lZ/TAD\nEkkWuTk5ZF3UgTa1ZrCtUnW+f/lZTunbT4WUJWGU4BERkYRw95fDjkFEZBcleAq0093X71F7SMXv\nRQ7Q4jkzmdf+dHot38y7R1XjjGmTaVmtZthhSZJTgkdERBLKzGoCtwONgfK72t29bWhBiUjK0TLp\nBZpjZhcC6WbWELgR+CLkmERKtbF330i9vz9NpxwYXa8WZ037igrVqoUdlqQAjQ0TEZFE+w8wD6gP\n3At8z68F90VEioVZ7FuKuQE4FtgOvAasB24ONSKRUmrzxp95u93vOOO+pzkkBz668Rq6LFqi5I4U\nG43gERGRRKvu7i+Y2U3uPgGYYGZK8IhIsUrBxE2sfuvufwX+GnYgIqXZtzMnUj7raprV/pEph1Sk\n0Yef0K7ZSWGHJSlGI3hERCTRdgaPy82sq5mdCOirLBEpVpZmMW8p5jEzm2dm95uZVrUVKaLcnBxG\nnNeaZR3aUCZ3K5uuHk7rtRs5QskdCYFG8IiISKI9YGZVgFuBp4HKwJ/CDUlEUo1G8OTP3duY2W+A\nPsBzZlYZeMPdHwg5NJES74e5s5jb/jR6L9vM/9LT2Nb1dY5t0SrssCSFaQSPiIgklLuPcvf17v61\nu7dx95PcPSvsuEQktaSlxb6lGndf4e5PAX8EZgF3hRySSIn3wb03s/mEE+m0bDNj6h5O7RU/UU/J\nHQmZRvCIiEhCmdmL5LPkrrtfEUI4IpKiUm/mVWzM7HfA+cA5wBrgDSIjLkUkH1s2rWfWs/347X3D\nOTgPxl3zBzo9MzjssEQAJXhERCTxRkXtlwd6ActCikVEUpSmaBVoCJGkTkd317/NIvsw491hHDLl\nblqm/8S7F7blpOsH0L5Fy7DDEvmFEjwiIpJQ7v5W9LGZvQ58FlI4IpKiLAWnXsXC3TWnRKQQebm5\nvPP7jrQc/hGzjyzPllffpMepXcMOS2QvSvCIiEhxawgcGnYQIpJaNIJnd2Y23N37mNlsdp9Ga4C7\ne5OQQhMpUZbMn83ss06hx5JNLEw3qvd/gmOV3JESSgkeERFJKDPbyO4fHlYAt4cUjoikKFOGZ083\nBY/dQo1CpAQbN+A2at37GJ13OmNrH8Zp07/i6EP1HZWUXErwiIhIQrl7pbBjEBFRfmd37r482L3W\n3XdLupvZQygRLylsy6b1fD3kOmpNe4saOc64qy6n46AhYYclUijNRhYRkYQys49iaRMRSSSz2LcU\n0z6fts7FHoVICTFz1BtMPONIMteMYn2XP1Bu6VLaK7kjpYRG8IiISEKYWXngIKCGmR1CpK4DQGWg\nVqz3mT/3wgREJyKpJgUTN/tkZtcA1wJHmdlXUacqAZ+HE5VIePJyc8m6uBPNh33IsQ6fXvl3zuzX\nP+ywRIpECR4REUmUq4GbgSOA6fya4NkA/CusoEQkNaUpwbOn14D3gX8Ad0S1b3T3teGEJBKOpd/O\n4ct2rej+40a+TzNmD3yaM6+5LuywRIpMCR4REUkId38SeNLMbnD3p8OOR0RSW0aaF94ptbi7f29m\ne32KNbNqSvJIqpgxZij0uowu25xxR9Sk5bRZHHXEEWGHJbJflOAREZFEyzOzqu7+M0AwXauvuz8T\nclwikkI0gmcvrxFZQWs6kZUOo39CDhwVRlAixWXzhnXMHnI9LX8exXvHV+eD4zrTYcjQsMMSOSBK\n8IiISKJd5e4Ddx24+zozuwpQgkdEio1WFtmdu3cLHuuHHYtIcfty9Jusv7Av1DMmXXMV7T99jLLl\nyocdlsgB03udiIgkWrrZr+VNzSwdKBtiPCKSgtLMY94KY2ZDzGylmX0d1XaPmS01s1nB1iXqXH8z\nW2Bm882sY1R7p6BtgZndEdVe38ymBO1vmFnC/s00s1PN7OBg/yIze9zM6ibq+UTClJeby8hLO1O9\n23m0Wp/D+kon0urqgUruSNJQgkdERBJtDPCGmbUzs3bA60QKe4qIFJs0i32LwUtAp3zan3D3psE2\nGsDMGgMXAMcG1zxjZulBsnsgkSXJGwN9g74ADwX3OhpYB1y5/6+8UM8CW8zsBOBW4DvglQQ+n0go\nli/8hvcbVOPsoWPIMWPWk09w9qdTwg5LJK6U4BERkUS7HfgY+GOwzQYqhBqRiKSctCJshXH3iUCs\nRYh7AMPcfbu7LwIWAM2DbYG7L3T3HcAwoEcw4rEt8GZw/ctAzxifa3/kuLsHcf4rmFJbKYHPJ1Ls\nZn7wKguvaUHXxRv4+Dc1qLb4B06+8eawwxKJOyV4REQkodw9D5gCfE/kA01bYF6YMYlI6inKCB4z\n62dm2VFbvxif5noz+yqYwnVI0FYL+DGqz5KgraD26sDP7p6zR3uibDSz/sDFwHtmlgaUieXCgqaY\n5dPvHDNzM8uMU8wiMdm6eSOj+7XhxC+u47DTGvDpww/QfvkqKteuHXZoIgmhIssiIpIQZtYI6Bts\nq4E3ANy9TZhxiUhqshhq6+zi7oOAQUV8imeB+4msQHU/8BhwRRHvEYbzgQuBK9x9RVB/55HCLoqa\nYtaeSBJqmpllufvcPfpVAm4ikugXKTZfjhnBzxecT/v1OYzq15EOT43kaNXakSRX6AieZCoiJyIi\nxeobIqN1urn7ae7+NJAbckwikqLiXINnL+7+k7vnBqMWBxMZsQiwFKgT1bV20FZQ+xqgqpll7NGe\nEO6+AvgPUMXMugHb3D2WtaLznWKWT7/7idQU2havmEX2JS83l3cu70a1rudw6vocxp7UhM5PZ6mQ\nsqSEWKZovUTyFJETEZHi0xtYDow3s8FBgeX9/OgkInJg4lmDJz9mdnjUYS9g15ejWcAFZlbOzOoD\nDYGpwDSgYfBlZ1kif0NnBfVwxgPnBtdfCryzn2HFEnefIJ7zgD7AFDM7d99XAQVPMYu+dzOgjru/\nF6dwRfZp1bLvee+YmnR96T3yMKY/9gjdsr8kvazGEEhqKHSKlrtPNLN6Md7vlyJywCIz21VEDoIM\nP4CZ7SoiN4/It7sXBn1eBu4hMsRVRERKMXcfCYwMlt/tAdwMHGpmzwJvu/sHoQYoIiklIy32KVqF\nMbPXgdZADTNbAtwNtDazpkSmaH0PXA3g7nPMbDgwF8gBrnP33OA+1wNjgXRgiLvPCZ7idmCYmT0A\nzAReiFvwe/srcLK7rwxiqgl8yK9FnvdLUMvnceCyGPr2A/oB1K2rFdpl/8wa9xpHfv4XDsrZxIRD\nq5E5bSZH6v9PkmIOpAbP9WZ2CZAN3Oru64hk7SdH9YnO5O+Z4W9B8ReRExGRYubum4HXgNeCoqPn\nEfnwogSPiBSbeK4s4u5982kuMAnj7gOAAfm0jwZG59O+kF+/JE20tF3JncAaYvtxFTTFbJdKwHHA\nJ5GFwfgNkGVm3d09O/pG0TWPMjMz45eJk5SwdfNG3u98MkeW/Z41ZzbmqPdGUv9Y1fOW1LS/73XP\nAg2ApkSG3z8Wt4j2IXpFg1WrVhXHU4qISBy5+zp3H+Tu7cKORURSS6Jr8JRiY8xsrJldZmaXAe+R\nT9IpH/lOMdt10t3Xu3sNd6/n7vWIfAm8V3JH5EDM/vAdJtepTu9P57M5O506t32m5I6ktP1K8IRV\nRC74UJDp7pk1a9bcn9BFREREJAWlmce8pRJ3vw14DmgSbIPc/fYYrssBdk0xmwcMD6aj3Wdm3RMZ\ns0hebi5ZV/WgcseenLFuJ6NOOJZTVqyhXPmDwg5NJFT7NUXLzA539+XB4Z5F5F4zs8eBI/i1iJwR\nZPiJJHAuAC50dzezXUXkhpHgInIiIiIikppScGTOPplZQ+BRIqPyZwN/dvcirdaV3xQzd7+rgL6t\n9y9Skd2tXraYGX/qTJfh81ieZkx7cADdbu8fdlgiJUKhCZ4kKyInIiIiIikonjV4ksQQYCgwETgb\neJrI6ociJVb2qBdpkH0XpzXawruZjWkzfBQt69cPOyyREiOWVbSSqYiciIiIiKSgVJt6FYNK7j44\n2J9vZjNCjUZkH7Zu3sj7XVvQfOI85l12NLVuf5de9zcNOyyREudAVtESERERESkVNEVrL+XN7EQi\npRQAKkQfu7sSPlIifD3+PVad25vea3fwVdkMDrtwIEceo+SOSH6U4BERERGRpKcEz16WA49HHa+I\nOnagbbFHJBIlLzeXUdedx/GD36ZxHrx33G/pMGU6ZQ5SIWWRgijBIyIiIiJJTzV4dufubcKOQaQg\nq5ctZtnQy6n61gTKOkz5+/107f+3sMMSKfGU4BERERGRpJeRpho8IqXBJwMfoOpn/+SYRsa0AXdy\nULvLaNWgQdhhiZQKSvCIiIiISNLTCB6Rkm3blk2MPrslbT6ew9Iyxk+zpnJG48ywwxIpVZTgERER\nEZGkpxo8IiXXnAnvs+KcnvRes4PZZTMoP2IE9ZTcESkyfZkhIiIiIknPzGPeUolFXGRmdwXHdc2s\nedhxSWrIy81l7D1XUaFtF9qs2cHoxo04Zs06GnY9O+zQREolJXhEREREJOmlWexbinkGaAX0DY43\nAgPDC0dSxeoVP/D1Ix1ou2MYSw8ux6R776bLnPmUrVgx7NBESi1N0RIRERGRpKdvNQvUwt2bmdlM\nAHdfZ2Zlww5KktvEf/8d+t/F0b+vxIwz7uK0n2/F0vRbKnKglOARERERkaSXlmJTr4pgp5mlAw5g\nZjWBvHBDkmS1bcsmRvc6hTM/mE15YFLZizirz21hhyWSNJTgEREREZGkl4JTr2L1FPA2cKiZDQDO\nBf4WbkiSjOZ+OpZl5/Sg96rtzCmTTsabb3JW955hhyWSVJTgEREREZGkpwRP/tz9P2Y2HWgHGNDT\n3eeFHJYkEc/LY8qwv7Pt5rs5a1Ue7x/TgLZTZ1CucuWwQxNJOkrwiIiIiEjSSw87gBLKzOoCW4B3\no9vc/YfwopJksXLJIhb+62Jalp/Npxe24NNKbeh8/4CwwxJJWkrwiIiIiEjSUw2eAr1HpP6OAeWB\n+sB84Ngwg5LS79PBD1Hupv6Uz3O+eOEBTuvbX4WURRJMCR4RERERSXoZ+lyZL3c/PvrYzJoB14YU\njiSBbVs28f45p3PamFlUBD7p0pFOSu6IFAsleEREREQk6aWrBk9M3H2GmbUIOw4pnb75/AN+7N2D\nXiu3Ma9MOqtfe43O5/YJOyyRlKEEj4iIiIgkPRVZzp+Z3RJ1mAY0A5aFFI6UUp6Xx5Q3/sHRUx+l\n/OptvN+wPm2zZ6mQskgxU4JHRERERJKeavAUqFLUfg6RmjxvhRSLlEKrli3mi56n0LHtBr75zSlU\n//JBOh93YthhiaQkJXhEREREJOlpBM/ezCwdqOTufw47FimdPhvyGGVu+As9tuQxouwJ9Jr4vmrt\niIRICR4RERERSXpaJn13Zpbh7jlmdmrYsUjps23rZkb3OYPT3ptBZYfRndrR670PlNwRCZkSPCIi\nIiKS9DSCZy9TidTbmWVmWcB/gc27Trr7iLACk5Jt0dxpzDvnLHp/s4H5GWmseuVVulzQN+ywRAQl\neEREREQkBagGT4HKA2uAtoADFjwqwSO7iRRSfpATv3mcn5uV4/28o2gzZTrlq1YNOzQRCWgMnYiI\niIgkvXSLfSuMmQ0xs5Vm9nVUWzUzG2dm3waPhwTtZmZPmdkCM/vKzJpFXXNp0P9bM7s0qv0kM5sd\nXPOUmSVi/NGhwQpaXwOzg8c5wePX+7pQUs/q5T+Q1ewIdl7/N+aVP4G6j8+g8/zvlNwRKWGU4BER\nERGRpJdmsW8xeAnotEfbHcBH7t4Q+Cg4BugMNAy2fsCzEEkIAXcDLYDmwN27kkJBn6uirtvzueIh\nHagYbJWi9ndtIgB89tI/+bZRfXp8+RMZOyvQ6Ko3qH5Y7bDDEpF8aIqWiIiIiCS9jDh+renuE82s\n3h7NPYDWwf7LwCfA7UH7UHd3YLKZVTWzw4O+49x9LYCZjQM6mdknQGV3nxy0DwV6Au/H7xUAsNzd\n74vzPSWJbNu6mfcvaM0p72ZT1WF02zPpNPZD0jL0EVKkpNJvp4iIiIgkvfTE1+A5zN2XB/srgMOC\n/VrAj1H9lgRt+2pfkk97vKnstBRo0dxpbH3xEk7P+oa1GWmsfPElulx0cdhhiUghCv0uI0nmGIuI\niIhICksrwmZm/cwsO2rrV5TnCkbrlPSqzu3CDkBKHs/LY+zdV3HY6x057ODNTL/zBmov/4njldwR\nKRViGaz6EqV/jrGIiIiIpLCi1OBx90Hunhm1DYrhKX4Kpl4RPK4M2pcCdaL61Q7a9tVeO5/2uNo1\nNUxkl9XLfyDrpFqcft/zjBuRgf/xczoOeIqDatQIOzQRiVGhCR53nwjs+QbQg8jcYoLHnlHtQz1i\nMrBrjnFHgjnG7r4O2DXH+HCCOcbBNx1Do+4lIiIiIhIXcS6ynJ8sYNco9UuBd6LaLwlGurcE1gdT\nucYCHczskOCLzw7A2ODcBjNrGYxsvyTqXiIJ8cUr/+J/jerTY9YKZlesQItXxlDjN3UKv1BESpT9\nrcETyhzjYHhsP4C6devuZ+giIiIikmriWYPHzF4nUiS5hpktITJS/UFguJldCSwG+gTdRwNdgAXA\nFuByiIygMbP7gWlBv/uiRtVcS2QUfQUixZXjXWBZBIgUUh5zSXtavDWJ6g6jW59Gp3HjVUhZpJQ6\n4N9cd3ezxFetC55rEDAIIDMzs6TPaxYRERGREuIARubsxd37FnBqr7o2wSj16wq4zxBgSD7t2cBx\nBxKjSGG+n5dN3n+vpP7m+WxMT2PV4OfpctnlYYclIgdgfxeMLFVzjEVEREQktRXDFK2UY2adzGx+\nsFjKHfmcv8XM5gaLr3xkZkeGEafszvPyeL//FSw691Sq5K2DPw+lweatNFFyR6TU298Ej+YYi4iI\niEipoQRPfJlZOjCQyCIrjYG+ZtZ4j24zgUx3bwK8CTxcvFHKntas+JGsk2tzxoMvcvzcHazv/Don\ntO1DetmyYYcmInEQyzLprwOTgGPMbEkwr/hBoL2ZfQucFRxDZI7xQiJzjAcTmT+8q0r/rjnG09h7\njvHzwTXfoTnGIiIiIhJn6Rb7JjFpDixw94XuvgMYRmTBlV+4+3h33xIcTmb3kftSzCa9/gzfNKpH\njxnLmXNweXZMncpRLU4NOywRiaNCa/BojrGIiIiIlHYZxVMyMpXkt4hKi330vxJ9kRuK7du2kP3v\n6zni1hepnQejTz+FTh9PUCFlkSSk32oREZEQXNRtABUOKkdaehrp6Wk88+rNvPTMGL6YMAdLM6oe\nUpHb7j2fGjWrMHzoeD56fyYAebm5/LBoJf/98F4qVzmIR+99gymfzqVqtYoMHn5byK9K4qF//yf5\n5JNpVK9ehVGjBgIwb95C7r77GbZv30F6ejr33HMNTZo0CjnS0kVTr8JjZhcBmcCZBZzXSrkJsvDL\nSXjWNZyau4gRpxzDhsv+TJcr/xB2WCKSIErwiIiIhOTR566hyiEH/3J83iWtuezaTgC8/fqnvDp4\nHDffeS59LmlDn0vaADBp4hxG/GcilascBECHszPp0edUHr779eJ/AZIQvXu346KLunL77U/80vbI\nIy9y3XUXcOaZmUyYkM0jj7zIK6/8I8QoSx9NvYq7ghZR2Y2ZnQX8FTjT3bfndyOtlBt/npfHmLuv\nps5Dz7PyxIPZ9I/n6X3PBWGHJSIJpgSPiIhICXFwxfK/7G/bugNj70+k48fMok3HE385btKsASuW\nrd2rn5ReJ598HEuW/H97dx4vRXWmcfz3sIsgKqhBkEDCkoBRVGRxi4oi4L7ELYnBkJgYUaPGEaMx\nBo1LyMSJxkncEBMVXGZURkHEBVQiqyKgEkURAVEREUFW4Z0/qi5p9r5wu+ve28+XT39u16lTVe/p\nbrqr3jp16uP1yiTx5ZfLAViy5Et2333XLEKr0mr4Eq2KNhFoI6kVSWLnTODs3AqS9gPuAHpGxCcb\nr8IKYeFHc3jpxIPoPmEuXwELOp/Dvkc6uWNWCpzgMTOzgpK0B3ADsGdE9ErvstItIu7JOLRMSdD/\ngjuR4NhTu3HsKV0BGHT7CJ59ahI7NqjHwDvOX2+ZFctXMemVGfS74uQsQrYM/frXP6Vv32u4+eZB\nrF27lqFDB2YdUpXjS7QqVkR8Jakfyd1yawKDIuINSQOASRExDBgINAAeSW6YywcRcUJmQZeAcQ/d\nwerzLuCkL9YwqX5dvjbqeY446KCswzKzItnW26SbmZnlazDJAcCe6fTbwC+3tICk8yRNkjTpwUFP\nFzi8bNxyTz/++uAl/P62nzDs4bFMffVdAH58QS8eHP4bjuy5P088NHa9Zca99CYd9m257vIsKx1D\nhgznyit/wpgx93LllT/hqqtuzTqkKse3Sa94ETE8ItpGxDcj4vdp2TVpcoeIOCoi9oiIjunDyZ0C\nWbliGeP++nO49SK6frGG4d06s9+iL2ju5I5ZSXGCx8zMCq1JRDwMrIXkrC+wZksLRMSdEdEpIjqd\n/eOexYix6Jrs3giAXXZtyMFH7M2/ps9Zb373Xvvz8vNT1ysbPXL9y7OsdDz22PP06JEcqPXqdQhT\np76dcURVT41yPMyqkndfG8vYM9rR9eMh6KyzmT1iOL3/OZ6adepkHZqZFZl/w8zMrNC+lNQYCABJ\nXYHF2YaUreXLV7LsyxXrnk8e9zYtW3+NuR8sWFfnn2PeYK+Wu6+b/nLJcqa++i7dDu9Q9Hgte7vv\nvisTJkwHYNy4qbRsuedWlrANSfk/zKqCsoGUl3U5hIOGzWV0k8vp0u9eWvfslXVoZpYRj8FjZmaF\ndhkwDPimpLHAbsBp2YaUrc8XLuXaXw0GYM2atRzRcz8OPOhb/O7y+5g7+xOkGuzRdGcu/vW/X6aX\nX5jOAV3bscMOdddb1+9/fT9TJ73L4s+/5Kxe13HOz3rQ66QuxWyOVbBLLx3IhAnTWLToCw47rA8X\nXng2113XjxtuuIuvvlpD3bp1GDCgX9ZhVjnO21h1smjBfMYc34Ujx89hLTD2J+fSvd/VWYdlZhlT\nRNW8o0CnTp1i0qRJ5V7OZ2WsTBX96JutR9LkiOiUdRxbI6kW0I7kGOtfEbE632U/WPp//t9a4lo0\naJd1CFYptN2uvbhJnz6V93dJpybHeo8xI9u6j19Kpo7+Hz4/+QwO+3wNr+5Ql91GjmKvQw/NOiwz\nq0Dbuo/vHjxmZlZQkqYCQ4GHIuLdrOMxs9LkcQmsqlu5Yhmv3XspXT8ewtMN6zC8XQeOeXGsx9ox\ns3Wc4DEzs0I7HjgDeFjSWuAh4OGI+CDbsMyslNSQOwNa1fXu6+N4+6SjadpuNeOPO4vDZ9xGvfoN\nsg7LzCoZn8wwM7OCjeT5/QAAIABJREFUiojZEfGHiDgAOBvYB5iVcVhmVmI8yLJVRbF2LSMH/IKl\nnbvR6/2lfDirGV363evkjpltknvwmJlZwUn6OkkvnjNIbpH+H9lGZGalxnkbq2oWLZjPiyd24fBX\n5iDguXN+QO/7/pF1WGZWiTnBY2ZmBSVpPFAbeAT4XkS8l3FIZlaCajjDY1XItBefYOE1P+LEVxbz\net06NHpqON27d886LDOr5JzgMTOzQjsnIv6VdRBmVtqc37GqYOWKZbzyXz/n8BVPMOu7zRi+66H0\nePARatWrl3VoZlYFOMFjZmYFIekHEXE/cKykYzecHxF/yiAsMytRHlvHKrv3pk1gxkndOfC9pYy6\ntBeHDHiIVjs2zDosM6tCPMiymZkVyo7p34abeHh0SDMrKpXjYVZMsXYtz/y+H18c2IXe7y3ljd0b\n0/miv7KDkztmVk7uwWNmZgUREXekT5+NiLG58yQdnEFIZlbCnLixyujzTz9izEld+e7Y2dQEnj37\nLLr/435Uw+fhzaz8/M1hZmaFdlueZWZmBVND+T/MimH6S0+w6i/daDJ9Dh/Urc3CUaM46oEHndwx\ns23mHjxmZlYQkroBBwG7Sbo0Z9ZOQM1sojKzUuW8jVUWq1au4OnzetN+9XiWf6sljf73cdp17U7t\n+vWzDs3MqjgneMzMrFDqkIy1U4tk3J0yXwCnZRKRmZWsGoqsQzBj1vQJvHXyUfSauYQJDeqx/13j\n+LrH2jGzCuIEj5mZFUREjAHGSBocEbOzjsfMSpvvomVZirVrefYPl9Lk2lvpvTIY02RX9p0wyQMp\nm1mFcoLHzMwKbZmkgUAHoF5ZYUQcmV1IZlZqPKqJZeXzTz9i3MW96PLgFGoDo878Hkc9MNRj7ZhZ\nhfO3ipmZFdoDwAygFfA74H1gYpYBmVnpkfJ/5Lc+vS9pmqQpkialZbtKGiXpnfTvLmm5JN0qaaak\nqZL2z1nPj9L670j6USHabtmZ/vIwVv2lGwc1n8Xk3XfhkxEjOHrIw07umFlB+JvFzMwKrXFE3AOs\njogxEfFjwL13zKyoVI5HORwRER0jolM63R94LiLaAM+l0wC9gDbp4zzgr5AkhIDfAl2AzsBvy5JC\nVrWtWrmCYX2PZnmPk1jwRS0+Ofspjvr4M77Rs2fWoZlZNbZdCR6fuTAzszysTv/Ol3SspP2AXbMM\nyMxKT0X34NmME4H70uf3ASfllP89EuOAnSU1BY4BRkXEZxGxCBgFOANQxb3/5iRG7bMHPQc9S7MV\nsHb/a2i978FZh2VmJaAixuA5IiI+zZkuO3Nxk6T+6fQVrH/mogvJmYsuOWcuOgEBTJY0LP2RM6u+\nPNqjlYlqf2eX6yU1Ai4DbiO5Tfol2YZkZqWmAL+6ATwjKYA7IuJOYI+ImJ/O/wjYI33eDJiTs+zc\ntGxz5VYFxdq1PPefl7PzNbdw7IrgxcY7s/crE/hOmzZZh2ZmJaIQgyyfCByePr8PGE2S4Fl35gIY\nJ6nszMXhpGcuACSVnbkYUoDYzMysyCLiyfTpYuCILGMxs9JVoxwZHknnkVxKVebONIGT65CImCdp\nd2CUpBm5MyMi0uSPlYDFCz/m3UF9aXDdcL69Ihh16skc9fCjHmvHzIpqexM8RT1zkftj26JFi+0M\n3czMikHSrZsoXgxMiognih2PmZWm8vTgSfdpN0zobFhnXvr3E0mPkYyh87GkphExPz2R+UlafR6w\nV87izdOyefz7xGhZ+ehyhGqVwOSnHqDhiP9g78bLGf2rHzN/vxM5+vjjsw7LzErQ9iZ4inrmIvfH\ntlOnTj4jYmZWNdQDvgU8kk6fCswC9pV0RET8MrPIzKxkVGRnGkk7AjUiYkn6vAcwABgG/Ai4Kf1b\nlsQeBvSTNJRkqILFaRJoJHBDzsDKPYArKyxQK6hVK1cw8sKTaD9oJJ/WrYlefp4e+x2WdVhmVsK2\nK8HjMxdmZpaHfYCDI2INgKS/Ai8BhwDTsgzMzEpHeS7RysMewGNKxtOrBTwYEU9Lmgg8LKkvMBs4\nPa0/HOgNzASWAecCRMRnkq4DJqb1BpQNW2CV2+y3JjP9lO70mLGYRYIF/a+hjZM7ZpaxbU7w+MyF\nmZnlaRegAcllWQA7ArtGxBpJK7MLy8xKSUXmdyLiPWDfTZQvBLpvojyACzazrkHAoAoMzwoo1q7l\nhduuouGVN3Ps8uDlXRrx7VfG07Vdu6xDMzPbrh48PnNhZmb5+AMwRdJokmOsw0gS+zsCz2YZmJmV\nDg91a9srGUj5J+w3ZzSLVsIzJx3P0f/zuAdSNrNKY5sTPD5zYWZm+YiIeyQNJ7mMF+DXEfFh+vzy\njMIysxKjAtwn3UrHqyOGsOCivhx8Wh2mH3gJ+31+Od9o2DDrsMzM1uN0s5mZFZSSrp7dgX3Tu2bV\nktR5K4uZmVUwleNhlli1cgVP/rwXDY8/m2NmLuflhSfR9YcDqOvkjplVQk7wmJlZof030A04K51e\nAtyeXThmVopUjn9mAB+8/TrP7N+Uo+54mp3Wwj+vvoqedw7OOiwzs83a3tukm5mZbU2XiNhf0msA\nEbFIUp2sgzKz0iL5vKblJ9auZdLjt7Hkgss47qM1vNKoIa3HvsJBHTpkHZqZ2RY5wWNmZoW2WlJN\nIAAk7QaszTYkMys97pljW7f4swW8c2cfDlzxMs8e3oaRS1rSY9hTHkjZzKoEf1OZmVmh3Qo8Buwu\n6ffAy8AN2YZkZqXGl2hVPEk9Jf1L0kxJ/Tcxv66kh9L54yW1LH6U+Xtt5MNM7NCcZX98mnHfuIgj\n75/OMU+OcHLHzKoM9+AxM7OCiogHJE0mGWhZwEkR8VbGYZlZyXHipiKlPTNvB44G5gITJQ2LiDdz\nqvUFFkVEa0lnAjcDZxQ/2i1bvWolI395Cm3uGs5+X8Ezrb/BIWf/lho1a2YdmplZuTjBY2ZmBRcR\nM4AZWcdhZqXLY/BUuM7AzIh4D0DSUOBEIDfBcyJwbfr8UeAvkhQRUcxAt+TzhZ/w8hHfovu0RSwV\n/LP/FfS48aaswzIrmNWrVzN37lxWrFiRdSgG1KtXj+bNm1O7du0KWZ8TPGZmVhCSlpCOu0Ny6rzs\neS2gTkT4N8jMikYemaCiNQPm5EzPBbpsrk5EfCVpMdAY+LQoEeZh0sCfcOi0RUzZqQHffGksB+2z\nT9YhmRXU3LlzadiwIS1btkRyz8YsRQQLFy5k7ty5tGrVqkLW6Z1rMzMriIhomDstqQFwAfAzkjF5\nzMyKxmPrVF6SzgPOA2jRokVRt71Hrz68tKo+vf9wPzVq+dDIqr8VK1Y4uVNJSKJx48YsWLCgwtbp\nUxlmZlZQknaWdC0wFWgIHBgRl2UblZmVnhrleFge5gF75Uw3T8s2WUdSLaARsHDDFUXEnRHRKSI6\n7bbbbgUKd9O+891TOO5PQ53csZLi5E7lUdHvhX/BzMysICQ1kXQj8CrwFbBfRFwdERvt3JuZFZqk\nvB+Wl4lAG0mtJNUBzgSGbVBnGPCj9PlpwPOVafwdM8vO448/jiRmzPj3EI2jR4/muOOOW69enz59\nePTRR4Fk/KD+/fvTpk0b9t9/f7p168aIESO2O5Ybb7yR1q1b065dO0aOHLnJOn369KFVq1Z07NiR\njh07MmXKFCC5zOqiiy6idevW7LPPPrz66qvrlunZsyc777zzRm0qJKeqzcysUGYDC4B7gWVA39wD\np4j4U0ZxmVlJcuKmIqVj6vQDRgI1gUER8YakAcCkiBgG3AP8Q9JM4DOSJJCZGUOGDOGQQw5hyJAh\n/O53v8trmd/85jfMnz+f6dOnU7duXT7++GPGjBmzXXG8+eabDB06lDfeeIMPP/yQo446irfffpua\nm7iL3sCBAznttNPWKxsxYgTvvPMO77zzDuPHj+f8889n/PjxAFx++eUsW7aMO+64Y7tiLA8neMzM\nrFAG8u+BlRtuqaKZWaF5DJ6KFxHDgeEblF2T83wF8L1ix2VmldvSpUt5+eWXeeGFFzj++OPzSvAs\nW7aMu+66i1mzZlG3bl0A9thjD04//fTtiuWJJ57gzDPPpG7durRq1YrWrVszYcIEunXrlvfy55xz\nDpLo2rUrn3/+OfPnz6dp06Z0796d0aNHb1d85eUEj5mZFUREXJtPPUlXRsSNBQ7HzEqeRyYwM9vQ\n4YcfvlHZ6aefzi9+8QuWLVtG7969N5rfp08f+vTpw6effrpRj5Z8EhpPPPEEPXv2pG3btjRu3JjJ\nkydzwAEHbHGZmTNn0qJFC3baaaetrv+SSy7hhRde2Kj8zDPPpH///uuVzZs3j65du66bbt68OfPm\nbTicWOKqq65iwIABdO/enZtuuom6desyb9489tprr42Wb9q06VbjLAQneMzMLGvfA5zgMbOCcg8e\nM7PKYciQIVx88cVAknQZMmQIBxxwwGbHQCvv2Gi33HLLdse4oRtvvJGvfe1rrFq1ivPOO4+bb76Z\na665ZusLFpkTPGZmljUfdZlZwXnwZDOzjW2px039+vW3OL9JkyblvgTps88+4/nnn2fatGlIYs2a\nNUhi4MCBNG7cmEWLFm1Uv0mTJrRu3ZoPPviAL774Yqu9eMrTg6dZs2bMmTNn3fTcuXNp1qzZRsuW\n9cipW7cu5557Ln/84x/LtXyxuK+qmZllzXdUMbMiUDkeZmZWCI8++ig//OEPmT17Nu+//z5z5syh\nVatWvPTSS7Rp04YPP/yQt956C4DZs2fz+uuv07FjR+rXr0/fvn25+OKLWbVqFQALFizgkUce2Wgb\nt9xyC1OmTNnosWFyB+CEE05g6NChrFy5klmzZvHOO+/QuXPnjerNnz8fSO6a9fjjj7P33nuvW/7v\nf/87EcG4ceNo1KhRZpdngXvwmJlZ9nw0ZWYFJza+I4qZmRXXkCFDuOKKK9YrO/XUUxkyZAiHHXYY\n999/P+eeey4rVqygdu3a3H333TRq1AiA66+/nquvvpr27dtTr149dtxxRwYMGLBd8XTo0IHTTz+d\n9u3bU6tWLW6//fZ1d9Dq3bs3d999N3vuuSff//73WbBgARFBx44d+dvf/rauzvDhw2ndujX169fn\n3nvvXbfuQw89lBkzZrB06VKaN2/OPffcwzHHHLNd8W6NIqrmidNOnTrFpEmTyr2ce+damcw/+v4w\nWpnt+DBKmhwRnSowmqKT9OuIuGFz8z9Y+n9Z/2+1jLVo0C7rEKxSaLtdP5yr1k7K+7ukTo1O/pHO\nyLbu45tZft566y2+/e1vZx2G5djUe7Kt+/juwWNmZgUh6Ta2cPlVRFyU/t1scsfMrOI4Z2NmZtWb\nEzxmZlYoPgVrZpWGPPSkmZlVc07wmJlZQUTEfVnHYGb2b+7BY2Zm1ZsTPGZmVlCSdgOuANoD9crK\nI+LIzIIys5IjJ3jMzIDkTlDyeKCVQkWPiey+qmZmVmgPAG8BrYDfAe8DE7MMyMxKj6S8H2Zm1VW9\nevVYuHBhhScWrPwigoULF1KvXr2tV86Te/CYmVmhNY6IeyRdHBFjgDGSnOAxsyLzeU0zs+bNmzN3\n7lwWLFiQdShGknBr3rx5ha2v0iR4JPUE/gzUBO6OiJsyDsnMzCrG6vTvfEnHAh8Cu2YYj5mVIF+i\nZWYGtWvXplWrVlmHYQVSKRI8kmoCtwNHA3OBiZKGRcSb2UZmZmYV4HpJjYDLgNuAnYBLsg3JzEqP\nEzxmZla9VYoED9AZmBkR7wFIGgqcCDjBY2ZWxUXEk+nTxcARWcZiZqUrOZ9oZmZWfVWWBE8zYE7O\n9FygS0axmJlZBZJ0L7DRSH4R8eMMwjGzEuVLtMzMrLqrLAmevEg6DzgvnVwq6V9ZxlPFNQE+zTqI\nLPkmGZVGyX8Wt/PD+PWKCqOAnsx5Xg84mWQcnry0aHB8yf9vlXReRNyZdRyWHX8GKkLbkv8uqQom\nT578qaTZRd5sKe2LuK3VT6m0E0qrre22ZSFVhtujSeoGXBsRx6TTVwJExI2ZBlaNSZoUEZ2yjsPM\nn8XSI6kG8HJEHJR1LFWF/5+YPwNmhVNK/7/c1uqnVNoJbms+Ksv9IicCbSS1klQHOBMYlnFMZmZW\nGG2A3bMOwszMzMysOqkUl2hFxFeS+gEjSW6TPigi3sg4LDMzqwCSlrD+GDwfAVdkFI6ZmZmZWbVU\nKRI8ABExHBiedRwlxNfxW2Xhz2I1FxENs46hGvD/E/NnwKxwSun/l9ta/ZRKO8Ft3apKMQaPmZlV\nX5Kei4juWyszMzMzM7NtV2l68JiZWfUiqR5QH2giaRdYd4/inYBmmQVmZmZmZlYNVZZBlq0AJPWU\n9C9JMyX138T8upIeSuePl9Sy+FFaKZA0SNInkqZvZr4k3Zp+FqdK2r/YMVpB/AyYDHwr/Vv2eAL4\nS4ZxmZlZCSqlfeM82nqppDfT/a7nJH09izi319bamVPvVEkhqcregSmftko6PX1f35D0YLFjrCh5\nfH5bSHpB0mvpZ7h3FnFur0IcIznBU01JqgncDvQC2gNnSWq/QbW+wKKIaA3cAtxc3CithAwGem5h\nfi+SOyu1Ac4D/lqEmKzAIuLPEdEK+FVEfCMiWqWPfSOiUiR4JO0h6UFJ70maLOkVSSdnHReApMGS\nTtvC/NHpzs/rksZKarcN2xguaef08Yuc8j0lPbqtsVd21eB9n5Qz3UnS6ALE0UfSnjnTd29iP8Ks\nyiilfeM82/oa0Cki9gEeBf5Q3Ci3X57tRFJD4GJgfHEjrDj5tFVSG+BK4OCI6AD8suiBVoA839er\ngYcjYj+SO3D/d3GjrDCDqeBjJCd4qq/OwMyIeC8iVgFDgRM3qHMicF/6/FGguyRhVsEi4kXgsy1U\nORH4eyTGATtLalqc6KwI1krauWxC0i65yYSspN93jwMvpgmoA0h2EppnG1m5fD8i9iX5Lh9Y3oUj\nondEfA7sDPwip/zDiNhskqEqqybv++6SehV4G32AdQmeiPhJRLxZ4G2aFVIp7Rtvta0R8UJELEsn\nx1G1vgPL5POeAlxHkqxbUczgKlg+bf0pcHtELAKIiE+KHGNFyaetQXLJP0Aj4MMixldhCnGM5ARP\n9dUMmJMzPZeNx7xYVycivgIWA42LEp3Z+vL5vFrV9dM0iQBAuuPx0wzjKXMksCoi/lZWEBGzI+K2\ntPfCul5Gkp6UdHj6vEfa4+NVSY9IapCW35TT3f2Padn3JE1Pe9m8mJbVlDRQ0sS07s/Sckn6S9or\n51lg93K05UWgdbqOgek2p0k6I113U0kvSpqSzjs0LX9fUhPgJuCb6fyBklqWdReWNE5Sh5zXYnTa\na2THtGvxBCVdpDe1U10ZVYf3fSBw1YaFW9hGDUn/LWmGpFFKem6dls67Jq0/XdKdaTynAZ2AB9LP\nxA457/vPJQ3M2ea610zSD9LPwxRJdyg5C2tWWZTSvnF596v6AiMKGlFhbLWdSi5p2SsinipmYAWQ\nz3vaFmirpFfvOElb6hlSmeXT1muBH0iaS3In7guLE1rRlfsYyQkeMzMrtJq5Z0DTg746GcZTpgPw\nankWSJMhVwNHRcT+wCTgUkmNgZOBDml39+vTRa4Bjkl72ZyQlvUFFkfEgcCBwE8ltUqXb0fSHfkc\n4KByhHY8MA04BegI7AscBQxUcqbnbGBkRJTNm7LB8v2BdyOiY0RcvsG8h4DT0/Y3BZpGxCSSBMPz\nEdEZOCLd1o7liDkr1eF9fwVYJemIDco3t41TgJbpNn4IdMtZ5i8RcWBE7A3sABwXEY+mbfx++plY\nnlP/f9KYy5wBDJX07fT5wennbA3w/TzaYmYZkvQDkoRuuXuBVnaSagB/Ai7LOpYiqUVyKc/hwFnA\nXcrpQV3NnAUMjojmQG/gH+n7XfL8IlRf84C9cqabp2WbrCOpFkn3toVFic5sffl8Xq3qehp4SFJ3\nSd2BIVTCM4WSbk97XEzcQrWuJAfJYyVNAX4EfJ3kLO8K4B5JpwBl3d7HAoMl/RQo683QAzgnXX48\nydnhNsBhwJCIWBMRHwLP5xH2A+l6DgZ+BRySs46PgTEkB/oTgXMlXQt8JyKW5LHuMg8DZZdrnU5y\n2UJZO/qn2x8N1ANalGO9lUIVfd8hSSZdvUHZ5rZxCPBIRKyNiI+AF3KWOULJYLLTSHo3dWALImIB\n8J6krmmC61tpe7sDBwAT0+13B76RZ1vMiqGU9o3z2q+SdBRJsv6EiFhZpNgq0tba2RDYGxgt6X2S\n7/JhqpoDLefzns4FhkXE6oiYBbxN8htQ1eTT1r4k+ydExCsk+yBNihJdcZX7GMkJnuprItBGUitJ\ndUjGFxi2QZ1hJDupkOy8Px8RUcQYzcoMIzkokaSuJGeg52cdlFWYK0gOWn+ePqaR9BTI2hvAursR\nRMQFJAeluwFfsf5vZL30r4BRaa+GjhHRPiL6pl35O5MkP44jSWoRET8nOQjfC5icHhALuDBnHa0i\n4pltbENZD4uTImLO5iql13gfRrJTMFjSOfluICLmAQsl7UPSQ+OhdJaAU3Pa0SIi3trGdhRTdXjf\niYjnSf4fdc0pLtc2JNUjGZjytIj4DnBXTpu3ZChJsu9U4LF030HAfTnbbhcR125T48wKo5T2jbfa\nVkn7AXeQJHeq6lgtW2xnRCyOiCYR0TIiWpKMNXRC2gu1qsnn8/s4Se+dsp6nbYH3ihlkBcmnrR+Q\n/HaT9iCtBywoapTFUe5jJCd4qql0p7MfMBJ4i2SU8TckDZBU1l38HqCxpJnApSRd9M0qnKQhJJcU\ntJM0V1LfdByHn6dVhpP8AM0kOcDIfABeqzgRsZakN8H7JAfDR5J8L2XteaCepPNzyuqnf98HOioZ\nu2Qvkrgh2Tk8WFJrACXj0LRVMh5Lo4gYDlxCchkUkr4ZEeMj4hqSHY+9SL6Xz5dUO63TNr206UXg\nDCXjqDQlueypvF7KWcduJEmdCUpuf/txRNwF3E1OgiO1hORM5+Y8BPxH2sapadlI4MKyy+/Sg4Wq\noDq979eTvC9lNreNscCpabv2ID0A4N/JnE/TtuQOrL2lz8RjJAM/nkWS7AF4DjhN0u7ptndVFb3t\nslVPpbRvnGdbBwINgEeUjJu14QF0pZdnO6uFPNs6kuSEzJskPTUvj4gq1wMtz7ZeRnIZ8uskPcP7\nVMVkbCGOkVQFXwczM6sCJLUlOQA8C/iUJEnwq4ioNAd96QH1LUAXkgPxL4G/kXT7vZ/kkpO3gF2A\nayNitKQjSe7GUTddzdUkZ5ueIDlgFvDHiLhP0v+SdI8WyQHwL9Pn15OMm6N0uycBXwC3AUeTnJla\nDQxKx0PZVOyjSV7P3Ftmi+RWt71I7jBxfUQ8JOlHwOXpOpcC50TErLTLeqeI+FTSg8A+JJfP3Q48\nmY7LQpoUmAdcFxG/S8t2AP6LZMyYGsCsiDgu7xc/Q9XpfZc0GVgSEYcrGX9gU9tYQtJT53CSwRoF\n3BwRoyRdT/J/9COS7vyzI+JaSacCNwDLScbsGbHBdp8E2kfEusuwlAzqfSXJ52E1cEEkd/0wMzOz\nInCCx8zMCkLSWpIeJX0jYmZa9l7uAaGZFYekBhGxNL1cbALJYMgfZR2XmZmZVZxaWQdgZmbV1ikk\n102/IOlpkks5tOVFzKxAnlRyN5U6JD2xnNwxMzOrZtyDx8zMCiodA6RsvI4jgb+TDMy6zQPMlhJJ\njwGtNii+IiJGZhGPFYffdzMzMysvJ3jMzKxoJO0CfA84IyK6Zx2PmZmZmVl14QSPmZmZmZmZmVkV\n59ukm5mZmZmZWYWTtCa9DXvZo+UW6i6tgO0NljQr3darkrptwzrultQ+ff7rDeb9c3tjTNdT9rpM\nl/R/6RhpW6rfUVLviti2VW/uwWNmZmZmZmYVTtLSiGhQ0XW3sI7BwJMR8aikHsAfI2Kf7Vjfdse0\ntfVKug94OyJ+v4X6fYBOEdGvomOx6sU9eMzMzMzMzKzgJDWQ9Fzau2aapBM3UaeppBdzergcmpb3\nkPRKuuwjkraWeHkRaJ0ue2m6rumSfpmW7SjpKUmvp+VnpOWjJXWSdBOwQxrHA+m8penfoZKOzYl5\nsKTTJNWUNFDSRElTJf0sj5flFaBZup7OaRtfk/RPSe0k1QEGAGeksZyRxj5I0oS07kavo5Um3ybd\nzMzMzMzMCmEHSVPS57NIbrRwckR8IakJME7SsFj/spKzgZER8XtJNYH6ad2rgaMi4ktJVwCXkiQ+\nNud4YJqkA4BzgS6AgPGSxgDfAD6MiGMBJDXKXTgi+kvqFxEdN7Huh4DTgafSBEx34HygL7A4Ig6U\nVBcYK+mZiJi1qQDT9nUH7kmLZgCHRsRXko4CboiIUyVdQ04PHkk3AM9HxI/Ty7smSHo2Ir7cwuth\nJcAJHjMzMzMzMyuE5bkJEkm1gRskHQasJem5sgfwUc4yE4FBad3HI2KKpO8C7UkSJgB1SHq+bMpA\nSVcDC0gSLt2Bx8qSH5L+FzgUeBr4T0k3k1zW9VI52jUC+HOaxOkJvBgRy9PLwvaRdFparxHQhiS5\nlass8dUMeAsYlVP/PkltgABqb2b7PYATJP0qna4HtEjXZSXMCR4zMzMzMzMrhu8DuwEHRMRqSe+T\nJCfWiYgX0wTQscBgSX8CFgGjIuKsPLZxeUQ8WjYhqfumKkXE25L2B3oD10t6LiK21CMod9kVkkYD\nxwBnAEPLNgdcGBEjt7KK5RHRUVJ9YCRwAXArcB3wQkScnA5IPXozyws4NSL+lU+8Vjo8Bo+ZmZmZ\nmZkVQyPgkzS5cwTw9Q0rSPo68HFE3AXcDewPjAMOllQ2ps6Oktrmuc2XgJMk1Ze0I3Ay8JKkPYFl\nEXE/MDDdzoZWpz2JNuUhkku/ynoDQZKsOb9sGUlt021uUkQsAy4CLpNUi+T1mZfO7pNTdQnQMGd6\nJHCh0u5Mkvbb3DastDjBY2ZmZmZmZsXwANBJ0jTgHJIxZzZ0OPC6pNdIesf8OSIWkCQ8hkiaSnJ5\n1rfy2WBEvApkZ2FgAAAAx0lEQVQMBiYA44G7I+I14DskY9dMAX4LXL+Jxe8EppYNsryBZ4DvAs9G\nxKq07G7gTeBVSdOBO9jKVTNpLFOBs4A/ADembc9d7gWgfdkgyyQ9fWqnsb2RTpv5NulmZmZmZmZm\nZlWde/CYmZmZmZmZmVVxTvCYmZmZmZmZmVVxTvCYmZmZmZmZmVVxTvCYmZmZmZmZmVVxTvCYmZmZ\nmZmZmVVxTvCYmZmZmZmZmVVxTvCYmZmZmZmZmVVxTvCYmZmZmZmZmVVx/w+p6ulxM9PMiAAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model_performance(target, predictions)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 348
    },
    "colab_type": "code",
    "id": "Zzrt9gSxyd7F",
    "outputId": "d28038fe-d7a6-4cd0-9841-ca2b7aea3bb0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.59\n"
     ]
    },
    {
     "data": {
      "image/png": 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tFxENeO4Ojj88aD8E+MjdfzPu2Mz6An0BmjRpcvSiRYuK/4L1s10CRfzUFynV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\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Duration: 2 seconds\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "lr_weight = LogisticRegression(class_weight=\"balanced\")\n",
    "predictions_weight_balanced = cross_val_predict(lr_weight, features, target, cv=3)\n",
    "model_performance(target, predictions_weight_balanced)\n",
    "print(f'\\nDuration: {time.time() - start_time:.0f} seconds') # print the time elapsed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 348
    },
    "colab_type": "code",
    "id": "S8Kfb5D8z-xf",
    "outputId": "d4cd78a8-a232-4cb4-946a-b42175d0fb18"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.55\n"
     ]
    },
    {
     "data": {
      "image/png": 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4aRts2sZTfT5kxL8fYVdePkuWr6XH3a/F8tGKhwjvomVmpQkld9519w+D4tVm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\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Duration: 2 seconds\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "penalty= {1:10,0:1}\n",
    "lr_weightp = LogisticRegression(class_weight=penalty)\n",
    "predictionsp = cross_val_predict(lr_weightp, features, target, cv=3)\n",
    "model_performance(target, predictionsp)\n",
    "print(f'\\nDuration: {time.time() - start_time:.0f} seconds') # print the time elapsed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "X_joQReAauMe"
   },
   "source": [
    "# LOGISTIC REGRESSION WITH SMOTE OVER SAMPLING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 348
    },
    "colab_type": "code",
    "id": "-KeaLil3fIoJ",
    "outputId": "f33d105e-6a65-4e1a-c71f-aa1c44fe3846"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.59\n"
     ]
    },
    {
     "data": {
      "image/png": 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Q2fv3kfrxy9RMHUGHnG/ZRC1mNL+VdgNvIrl6rWinl6d9u8I/b8pXrQpPPMGq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\ngg==\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Duration: 3 seconds\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "smote = SMOTE(ratio='minority')\n",
    "features_sm, target_sm = smote.fit_sample(features, target)\n",
    "predictions_sm = cross_val_predict(lr, features_sm, target_sm, cv=3)\n",
    "model_performance(pd.Series(target_sm), pd.Series(predictions_sm))\n",
    "print(f'\\nDuration: {time.time() - start_time:.0f} seconds') # print the time elapsed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Odtocy2zxyKR"
   },
   "source": [
    "# SCALING AND NORMALIZING THE DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "rCDEEf_B12FN"
   },
   "outputs": [],
   "source": [
    "def normalize(subset):\n",
    "   continious_columns = subset.select_dtypes(include=['float']).columns\n",
    "   mm_scaler = preprocessing.MinMaxScaler()\n",
    "   for col in continious_columns:\n",
    "     subset[col]= mm_scaler.fit_transform(subset[[col]])\n",
    "   return subset\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Hkzbl5yQ2MZt"
   },
   "outputs": [],
   "source": [
    "lr = LogisticRegression()\n",
    "scaled_data = normalize(data)\n",
    "features_scaled = scaled_data.drop(columns=['loan_status'],axis=1)\n",
    "target_scaled = scaled_data['loan_status']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 314
    },
    "colab_type": "code",
    "id": "qCThv2sg3pkn",
    "outputId": "8ecc641e-ed8d-4102-e35e-dea4ce3c441b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.6\n"
     ]
    },
    {
     "data": {
      "image/png": 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oyhIeiTDhoovo+MEH7DAj48476XbffTFKXrKowCMiIiIi8U1z8IiIhGLXjm3MHPEEJ333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\nSUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rus = RandomUnderSampler(random_state=0)\n",
    "rus.fit(features_scaled, target_scaled)\n",
    "features_sc, target_sc = rus.fit_resample(features_scaled, target_scaled)\n",
    "predictions_sc = cross_val_predict(lr, features_sc, target_sc, cv=3)\n",
    "model_performance(pd.Series(target_sc), pd.Series(predictions_sc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "aggRlbBURAXP"
   },
   "source": [
    "# XGBOOST CLASSIFIER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 721
    },
    "colab_type": "code",
    "id": "3yYHhsvJsGZG",
    "outputId": "47e05330-3fb9-4293-a67f-26233ca631cb"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Mi4iIiMiN0ZoHuWnc3d159dVX+fLLLykoKGD8+PH079+f9PR0QkJCSElJAajw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\nAABARP4FtCRfhX/vNNoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 792x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_correlation_heatmap(df):\n",
    "    corr = df.corr()\n",
    "    sns.set(style=\"white\")\n",
    "    mask = np.zeros_like(corr, dtype=np.bool)\n",
    "    mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "    f, ax = plt.subplots(figsize=(11, 9))\n",
    "    cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "\n",
    "\n",
    "    sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n",
    "    plt.show()\n",
    "plot_correlation_heatmap(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 255
    },
    "colab_type": "code",
    "id": "4bipwfl62Fze",
    "outputId": "44c4f9b4-aa1a-467f-9717-c4ca1c03c658"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['loan_amnt', 'int_rate', 'installment', 'annual_inc', 'dti',\n",
       "       'delinq_2yrs', 'inq_last_6mths', 'open_acc', 'pub_rec', 'revol_bal',\n",
       "       'revol_util', 'total_acc', 'home_ownership_MORTGAGE',\n",
       "       'home_ownership_NONE', 'home_ownership_OTHER', 'home_ownership_OWN',\n",
       "       'home_ownership_RENT', 'verification_status_Not Verified',\n",
       "       'verification_status_Source Verified', 'verification_status_Verified',\n",
       "       'purpose_car', 'purpose_credit_card', 'purpose_debt_consolidation',\n",
       "       'purpose_educational', 'purpose_home_improvement', 'purpose_house',\n",
       "       'purpose_major_purchase', 'purpose_medical', 'purpose_moving',\n",
       "       'purpose_other', 'purpose_renewable_energy', 'purpose_small_business',\n",
       "       'purpose_vacation', 'purpose_wedding', 'term_ 36 months',\n",
       "       'term_ 60 months', 'emp_length_beginner', 'emp_length_experienced',\n",
       "       'emp_length_intermediate'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 41,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "PF2QsfQP1QZA"
   },
   "outputs": [],
   "source": [
    "features_corr = features.drop(columns=['home_ownership_RENT','term_ 60 months','home_ownership_NONE', 'purpose_car', 'purpose_credit_card', 'purpose_debt_consolidation',\n",
    "       'purpose_educational', 'purpose_home_improvement', 'purpose_house',\n",
    "       'purpose_major_purchase', 'purpose_medical', 'purpose_moving',\n",
    "       'purpose_other', 'purpose_renewable_energy', 'purpose_small_business',\n",
    "       'purpose_vacation', 'purpose_wedding'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "CFDI7DTF3jKx",
    "outputId": "9d34aba6-7483-4be0-b1a7-fa44b3155683"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(37675, 22)\n",
      "(37675,)\n"
     ]
    }
   ],
   "source": [
    "print(features_corr.shape)\n",
    "print(target.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "8rQ0_vMO2zIS",
    "outputId": "2d784e6d-d12a-496f-dbc5-46dc36bbca2b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Duration: 0 seconds\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "smote = SMOTE(ratio='minority')\n",
    "features_c, target_c = smote.fit_sample(features_corr, target)\n",
    "print(f'\\nDuration: {time.time() - start_time:.0f} seconds') # print the time elapsed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 289
    },
    "colab_type": "code",
    "id": "8TR7mnxdEknu",
    "outputId": "5aa9946e-2994-408f-a272-41f0d92ecd6b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 8 candidates, totalling 24 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 2 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done   1 tasks      | elapsed:    6.6s\n",
      "[Parallel(n_jobs=-1)]: Done   4 tasks      | elapsed:   11.5s\n",
      "[Parallel(n_jobs=-1)]: Done   9 tasks      | elapsed:   32.4s\n",
      "[Parallel(n_jobs=-1)]: Done  14 tasks      | elapsed:   45.2s\n",
      "[Parallel(n_jobs=-1)]: Done  21 tasks      | elapsed:  1.2min\n",
      "[Parallel(n_jobs=-1)]: Done  24 out of  24 | elapsed:  1.3min remaining:    0.0s\n",
      "[Parallel(n_jobs=-1)]: Done  24 out of  24 | elapsed:  1.3min finished\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "              colsample_bynode=1, colsample_bytree=1, gamma=0,\n",
       "              learning_rate=0.16, max_delta_step=0, max_depth=5,\n",
       "              min_child_weight=6, missing=None, n_estimators=100, n_jobs=1,\n",
       "              nthread=None, objective='binary:logistic', random_state=0,\n",
       "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,\n",
       "              silent=None, subsample=1, verbosity=1)"
      ]
     },
     "execution_count": 45,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import xgboost as xgb\n",
    "X_train, X_test, Y_train, Y_test = train_test_split(features_c, target_c, test_size=0.33)\n",
    "model = xgb.XGBClassifier()\n",
    "param_dist = {\"max_depth\": [3,5],\n",
    "              \"min_child_weight\" : [3,6],\n",
    "              \"n_estimators\": [100],\n",
    "              \"learning_rate\": [0.05,.16],}\n",
    "grid_search = GridSearchCV(model, param_grid=param_dist, cv = 3, \n",
    "                                   verbose=10, n_jobs=-1, scoring=\"f1\")\n",
    "grid_search.fit(X_train, Y_train)\n",
    "\n",
    "grid_search.best_estimator_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "7ID5IDVF09zK"
   },
   "source": [
    "# **XGBOOST HYPERPARAMETER**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "oQsh_P9CfEqy"
   },
   "source": [
    "*   1)objective='binary:logistic' for binary classification and 'objective': 'multi:softmax' softmax for multiclass classification you also need to set num_class(number of classes)\n",
    "*   2)subsample=0.8 = subsample, which is for each tree the % of rows taken to build the tree.\n",
    "*   3)colsample_bytree: number of columns used by each tree.\n",
    "*   4)max_depth = It represents the depth of each tree, which is the maximum number of different features used in each tree.\n",
    "*   5)n_estimator = maximun number of decision tress.\n",
    "*   6) booster parameter allows you to set the type of model you will use when building the ensemble. The default is gbtree which builds an ensemble of decision trees. If your data isn’t too complicated, you can go with the faster and simpler gblinear option which builds an ensemble of linear models.\n",
    "*   7) The gamma parameter can also help with controlling overfitting. It specifies the minimum reduction in the loss required to make a further partition on a leaf node of the tree.\n",
    "*   8)scoring: \"f1\" pr \"accuracy\"\n",
    "*   9)scale_pos_weight parameter impose greater penalties for errors on the minor class\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "m2C4d-jQG5_O",
    "outputId": "f2c500f9-13b0-4b42-a35a-5dec0f1f4a49"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Duration: 0 seconds\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "start_time = time.time()\n",
    "model = xgb.XGBClassifier(learning_rate=0.01, max_depth=7, n_estimators=100,  gamma=5,colsample_bytree=.6, subsample=0.8, scoring = 'f1',scale_pos_weight=1)\n",
    "print(f'\\nDuration: {time.time() - start_time:.0f} seconds') # print the time elapsed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "bL6HAXjKHAGR",
    "outputId": "4fa7022c-2e60-42a8-b900-046cfd0c6d0e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0]\tvalidation_0-auc:0.911969\tvalidation_0-error:0.140258\tvalidation_1-auc:0.906473\tvalidation_1-error:0.148529\n",
      "[1]\tvalidation_0-auc:0.937461\tvalidation_0-error:0.106095\tvalidation_1-auc:0.934361\tvalidation_1-error:0.111549\n",
      "[2]\tvalidation_0-auc:0.940877\tvalidation_0-error:0.104916\tvalidation_1-auc:0.936781\tvalidation_1-error:0.108311\n",
      "[3]\tvalidation_0-auc:0.945051\tvalidation_0-error:0.100086\tvalidation_1-auc:0.940681\tvalidation_1-error:0.102492\n",
      "[4]\tvalidation_0-auc:0.945188\tvalidation_0-error:0.101773\tvalidation_1-auc:0.940716\tvalidation_1-error:0.105073\n",
      "[5]\tvalidation_0-auc:0.946408\tvalidation_0-error:0.099415\tvalidation_1-auc:0.942199\tvalidation_1-error:0.101319\n",
      "[6]\tvalidation_0-auc:0.946403\tvalidation_0-error:0.098884\tvalidation_1-auc:0.94188\tvalidation_1-error:0.101225\n",
      "[7]\tvalidation_0-auc:0.946731\tvalidation_0-error:0.099762\tvalidation_1-auc:0.942336\tvalidation_1-error:0.102867\n",
      "[8]\tvalidation_0-auc:0.946652\tvalidation_0-error:0.100409\tvalidation_1-auc:0.942482\tvalidation_1-error:0.1039\n",
      "[9]\tvalidation_0-auc:0.946687\tvalidation_0-error:0.10071\tvalidation_1-auc:0.942603\tvalidation_1-error:0.104557\n",
      "[10]\tvalidation_0-auc:0.94663\tvalidation_0-error:0.102351\tvalidation_1-auc:0.942428\tvalidation_1-error:0.10634\n",
      "[11]\tvalidation_0-auc:0.946766\tvalidation_0-error:0.102466\tvalidation_1-auc:0.942767\tvalidation_1-error:0.106856\n",
      "[12]\tvalidation_0-auc:0.946973\tvalidation_0-error:0.101311\tvalidation_1-auc:0.943171\tvalidation_1-error:0.105355\n",
      "[13]\tvalidation_0-auc:0.947395\tvalidation_0-error:0.099623\tvalidation_1-auc:0.943723\tvalidation_1-error:0.103712\n",
      "[14]\tvalidation_0-auc:0.947541\tvalidation_0-error:0.0996\tvalidation_1-auc:0.943749\tvalidation_1-error:0.103712\n",
      "[15]\tvalidation_0-auc:0.947683\tvalidation_0-error:0.098375\tvalidation_1-auc:0.943886\tvalidation_1-error:0.10282\n",
      "[16]\tvalidation_0-auc:0.94818\tvalidation_0-error:0.097427\tvalidation_1-auc:0.944304\tvalidation_1-error:0.1016\n",
      "[17]\tvalidation_0-auc:0.948016\tvalidation_0-error:0.098075\tvalidation_1-auc:0.944288\tvalidation_1-error:0.102304\n",
      "[18]\tvalidation_0-auc:0.947863\tvalidation_0-error:0.098814\tvalidation_1-auc:0.944176\tvalidation_1-error:0.103196\n",
      "[19]\tvalidation_0-auc:0.948009\tvalidation_0-error:0.098121\tvalidation_1-auc:0.944241\tvalidation_1-error:0.102257\n",
      "[20]\tvalidation_0-auc:0.947861\tvalidation_0-error:0.098791\tvalidation_1-auc:0.944165\tvalidation_1-error:0.103149\n",
      "[21]\tvalidation_0-auc:0.947958\tvalidation_0-error:0.097843\tvalidation_1-auc:0.944289\tvalidation_1-error:0.102023\n",
      "[22]\tvalidation_0-auc:0.947906\tvalidation_0-error:0.098352\tvalidation_1-auc:0.94422\tvalidation_1-error:0.102773\n",
      "[23]\tvalidation_0-auc:0.947952\tvalidation_0-error:0.098652\tvalidation_1-auc:0.944155\tvalidation_1-error:0.103149\n",
      "[24]\tvalidation_0-auc:0.947869\tvalidation_0-error:0.099623\tvalidation_1-auc:0.944038\tvalidation_1-error:0.104228\n",
      "[25]\tvalidation_0-auc:0.9482\tvalidation_0-error:0.098722\tvalidation_1-auc:0.944455\tvalidation_1-error:0.10282\n",
      "[26]\tvalidation_0-auc:0.948199\tvalidation_0-error:0.099115\tvalidation_1-auc:0.944434\tvalidation_1-error:0.103571\n",
      "[27]\tvalidation_0-auc:0.948462\tvalidation_0-error:0.098491\tvalidation_1-auc:0.944692\tvalidation_1-error:0.102773\n",
      "[28]\tvalidation_0-auc:0.948533\tvalidation_0-error:0.09886\tvalidation_1-auc:0.944617\tvalidation_1-error:0.103055\n",
      "[29]\tvalidation_0-auc:0.948381\tvalidation_0-error:0.099092\tvalidation_1-auc:0.944491\tvalidation_1-error:0.103618\n",
      "[30]\tvalidation_0-auc:0.94863\tvalidation_0-error:0.098606\tvalidation_1-auc:0.944735\tvalidation_1-error:0.102633\n",
      "[31]\tvalidation_0-auc:0.948756\tvalidation_0-error:0.098537\tvalidation_1-auc:0.944866\tvalidation_1-error:0.10268\n",
      "[32]\tvalidation_0-auc:0.948938\tvalidation_0-error:0.098051\tvalidation_1-auc:0.945042\tvalidation_1-error:0.102445\n",
      "[33]\tvalidation_0-auc:0.949225\tvalidation_0-error:0.09715\tvalidation_1-auc:0.945249\tvalidation_1-error:0.101506\n",
      "[34]\tvalidation_0-auc:0.949215\tvalidation_0-error:0.09752\tvalidation_1-auc:0.945223\tvalidation_1-error:0.101976\n",
      "[35]\tvalidation_0-auc:0.949388\tvalidation_0-error:0.097312\tvalidation_1-auc:0.945312\tvalidation_1-error:0.101835\n",
      "[36]\tvalidation_0-auc:0.949422\tvalidation_0-error:0.09685\tvalidation_1-auc:0.945353\tvalidation_1-error:0.101459\n",
      "[37]\tvalidation_0-auc:0.949482\tvalidation_0-error:0.09678\tvalidation_1-auc:0.945368\tvalidation_1-error:0.101084\n",
      "[38]\tvalidation_0-auc:0.949567\tvalidation_0-error:0.096433\tvalidation_1-auc:0.945461\tvalidation_1-error:0.100849\n",
      "[39]\tvalidation_0-auc:0.949756\tvalidation_0-error:0.095624\tvalidation_1-auc:0.945603\tvalidation_1-error:0.09977\n",
      "[40]\tvalidation_0-auc:0.949745\tvalidation_0-error:0.096017\tvalidation_1-auc:0.945578\tvalidation_1-error:0.100239\n",
      "[41]\tvalidation_0-auc:0.949652\tvalidation_0-error:0.096179\tvalidation_1-auc:0.945521\tvalidation_1-error:0.100427\n",
      "[42]\tvalidation_0-auc:0.949583\tvalidation_0-error:0.09641\tvalidation_1-auc:0.945464\tvalidation_1-error:0.100756\n",
      "[43]\tvalidation_0-auc:0.949691\tvalidation_0-error:0.095856\tvalidation_1-auc:0.945593\tvalidation_1-error:0.100239\n",
      "[44]\tvalidation_0-auc:0.949767\tvalidation_0-error:0.095648\tvalidation_1-auc:0.945665\tvalidation_1-error:0.099488\n",
      "[45]\tvalidation_0-auc:0.949857\tvalidation_0-error:0.095486\tvalidation_1-auc:0.945696\tvalidation_1-error:0.099301\n",
      "[46]\tvalidation_0-auc:0.949885\tvalidation_0-error:0.09507\tvalidation_1-auc:0.945753\tvalidation_1-error:0.099066\n",
      "[47]\tvalidation_0-auc:0.949864\tvalidation_0-error:0.095\tvalidation_1-auc:0.945746\tvalidation_1-error:0.098785\n",
      "[48]\tvalidation_0-auc:0.949959\tvalidation_0-error:0.094954\tvalidation_1-auc:0.945756\tvalidation_1-error:0.098597\n",
      "[49]\tvalidation_0-auc:0.949941\tvalidation_0-error:0.095162\tvalidation_1-auc:0.945709\tvalidation_1-error:0.098785\n",
      "[50]\tvalidation_0-auc:0.94993\tvalidation_0-error:0.095255\tvalidation_1-auc:0.945679\tvalidation_1-error:0.099019\n",
      "[51]\tvalidation_0-auc:0.949979\tvalidation_0-error:0.094954\tvalidation_1-auc:0.945699\tvalidation_1-error:0.098691\n",
      "[52]\tvalidation_0-auc:0.949993\tvalidation_0-error:0.094862\tvalidation_1-auc:0.945748\tvalidation_1-error:0.098221\n",
      "[53]\tvalidation_0-auc:0.949994\tvalidation_0-error:0.094538\tvalidation_1-auc:0.945784\tvalidation_1-error:0.097893\n",
      "[54]\tvalidation_0-auc:0.950044\tvalidation_0-error:0.094515\tvalidation_1-auc:0.945815\tvalidation_1-error:0.097705\n",
      "[55]\tvalidation_0-auc:0.949985\tvalidation_0-error:0.094654\tvalidation_1-auc:0.945822\tvalidation_1-error:0.098081\n",
      "[56]\tvalidation_0-auc:0.950093\tvalidation_0-error:0.094469\tvalidation_1-auc:0.945939\tvalidation_1-error:0.097846\n",
      "[57]\tvalidation_0-auc:0.950102\tvalidation_0-error:0.094376\tvalidation_1-auc:0.945984\tvalidation_1-error:0.097564\n",
      "[58]\tvalidation_0-auc:0.950092\tvalidation_0-error:0.094469\tvalidation_1-auc:0.945964\tvalidation_1-error:0.097658\n",
      "[59]\tvalidation_0-auc:0.950207\tvalidation_0-error:0.094515\tvalidation_1-auc:0.946005\tvalidation_1-error:0.097705\n",
      "[60]\tvalidation_0-auc:0.950228\tvalidation_0-error:0.094353\tvalidation_1-auc:0.946022\tvalidation_1-error:0.097658\n",
      "[61]\tvalidation_0-auc:0.950234\tvalidation_0-error:0.094469\tvalidation_1-auc:0.945985\tvalidation_1-error:0.097705\n",
      "[62]\tvalidation_0-auc:0.950221\tvalidation_0-error:0.094538\tvalidation_1-auc:0.945964\tvalidation_1-error:0.097705\n",
      "[63]\tvalidation_0-auc:0.950312\tvalidation_0-error:0.094422\tvalidation_1-auc:0.945931\tvalidation_1-error:0.097705\n",
      "[64]\tvalidation_0-auc:0.950276\tvalidation_0-error:0.094399\tvalidation_1-auc:0.945918\tvalidation_1-error:0.097705\n",
      "[65]\tvalidation_0-auc:0.950244\tvalidation_0-error:0.094538\tvalidation_1-auc:0.945886\tvalidation_1-error:0.097846\n",
      "[66]\tvalidation_0-auc:0.950245\tvalidation_0-error:0.094561\tvalidation_1-auc:0.945866\tvalidation_1-error:0.09794\n",
      "[67]\tvalidation_0-auc:0.950264\tvalidation_0-error:0.094723\tvalidation_1-auc:0.945863\tvalidation_1-error:0.098128\n",
      "[68]\tvalidation_0-auc:0.950321\tvalidation_0-error:0.094607\tvalidation_1-auc:0.945905\tvalidation_1-error:0.097752\n",
      "[69]\tvalidation_0-auc:0.950343\tvalidation_0-error:0.094492\tvalidation_1-auc:0.945925\tvalidation_1-error:0.097846\n",
      "[70]\tvalidation_0-auc:0.950384\tvalidation_0-error:0.094515\tvalidation_1-auc:0.945956\tvalidation_1-error:0.09794\n",
      "[71]\tvalidation_0-auc:0.950465\tvalidation_0-error:0.094515\tvalidation_1-auc:0.946001\tvalidation_1-error:0.097987\n",
      "[72]\tvalidation_0-auc:0.950595\tvalidation_0-error:0.094376\tvalidation_1-auc:0.94609\tvalidation_1-error:0.097799\n",
      "[73]\tvalidation_0-auc:0.950607\tvalidation_0-error:0.094399\tvalidation_1-auc:0.946088\tvalidation_1-error:0.097705\n",
      "[74]\tvalidation_0-auc:0.950646\tvalidation_0-error:0.094284\tvalidation_1-auc:0.946135\tvalidation_1-error:0.097611\n",
      "[75]\tvalidation_0-auc:0.950704\tvalidation_0-error:0.094284\tvalidation_1-auc:0.946172\tvalidation_1-error:0.097611\n",
      "[76]\tvalidation_0-auc:0.950715\tvalidation_0-error:0.094492\tvalidation_1-auc:0.946154\tvalidation_1-error:0.097799\n",
      "[77]\tvalidation_0-auc:0.950738\tvalidation_0-error:0.094261\tvalidation_1-auc:0.946177\tvalidation_1-error:0.097705\n",
      "[78]\tvalidation_0-auc:0.950736\tvalidation_0-error:0.094214\tvalidation_1-auc:0.946154\tvalidation_1-error:0.097705\n",
      "[79]\tvalidation_0-auc:0.950801\tvalidation_0-error:0.094238\tvalidation_1-auc:0.946175\tvalidation_1-error:0.097752\n",
      "[80]\tvalidation_0-auc:0.950826\tvalidation_0-error:0.09433\tvalidation_1-auc:0.946163\tvalidation_1-error:0.097705\n",
      "[81]\tvalidation_0-auc:0.950859\tvalidation_0-error:0.094307\tvalidation_1-auc:0.946201\tvalidation_1-error:0.097611\n",
      "[82]\tvalidation_0-auc:0.950875\tvalidation_0-error:0.094238\tvalidation_1-auc:0.946174\tvalidation_1-error:0.097658\n",
      "[83]\tvalidation_0-auc:0.950908\tvalidation_0-error:0.094261\tvalidation_1-auc:0.946164\tvalidation_1-error:0.097611\n",
      "[84]\tvalidation_0-auc:0.95094\tvalidation_0-error:0.094284\tvalidation_1-auc:0.946168\tvalidation_1-error:0.097658\n",
      "[85]\tvalidation_0-auc:0.950937\tvalidation_0-error:0.094422\tvalidation_1-auc:0.946164\tvalidation_1-error:0.097752\n",
      "[86]\tvalidation_0-auc:0.950922\tvalidation_0-error:0.094492\tvalidation_1-auc:0.946155\tvalidation_1-error:0.097846\n",
      "[87]\tvalidation_0-auc:0.951011\tvalidation_0-error:0.094214\tvalidation_1-auc:0.946205\tvalidation_1-error:0.097752\n",
      "[88]\tvalidation_0-auc:0.951006\tvalidation_0-error:0.094261\tvalidation_1-auc:0.946196\tvalidation_1-error:0.097752\n",
      "[89]\tvalidation_0-auc:0.951065\tvalidation_0-error:0.094376\tvalidation_1-auc:0.946212\tvalidation_1-error:0.097752\n",
      "[90]\tvalidation_0-auc:0.951084\tvalidation_0-error:0.094422\tvalidation_1-auc:0.946214\tvalidation_1-error:0.097799\n",
      "[91]\tvalidation_0-auc:0.951075\tvalidation_0-error:0.094399\tvalidation_1-auc:0.946215\tvalidation_1-error:0.09794\n",
      "[92]\tvalidation_0-auc:0.951086\tvalidation_0-error:0.094422\tvalidation_1-auc:0.946232\tvalidation_1-error:0.09794\n",
      "[93]\tvalidation_0-auc:0.951141\tvalidation_0-error:0.09433\tvalidation_1-auc:0.946289\tvalidation_1-error:0.097752\n",
      "[94]\tvalidation_0-auc:0.95118\tvalidation_0-error:0.094422\tvalidation_1-auc:0.946297\tvalidation_1-error:0.097705\n",
      "[95]\tvalidation_0-auc:0.951213\tvalidation_0-error:0.094307\tvalidation_1-auc:0.946311\tvalidation_1-error:0.097658\n",
      "[96]\tvalidation_0-auc:0.951227\tvalidation_0-error:0.094261\tvalidation_1-auc:0.946337\tvalidation_1-error:0.097517\n",
      "[97]\tvalidation_0-auc:0.951255\tvalidation_0-error:0.094053\tvalidation_1-auc:0.946358\tvalidation_1-error:0.097424\n",
      "[98]\tvalidation_0-auc:0.951285\tvalidation_0-error:0.09403\tvalidation_1-auc:0.946375\tvalidation_1-error:0.097377\n",
      "[99]\tvalidation_0-auc:0.9513\tvalidation_0-error:0.094238\tvalidation_1-auc:0.946365\tvalidation_1-error:0.097471\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "              colsample_bynode=1, colsample_bytree=0.6, gamma=5,\n",
       "              learning_rate=0.01, max_delta_step=0, max_depth=7,\n",
       "              min_child_weight=1, missing=None, n_estimators=100, n_jobs=1,\n",
       "              nthread=None, objective='binary:logistic', random_state=0,\n",
       "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, scoring='f1',\n",
       "              seed=None, silent=None, subsample=0.8, verbosity=1)"
      ]
     },
     "execution_count": 47,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_set = [(X_train, Y_train), (X_test, Y_test)]\n",
    "eval_metric = [\"auc\",\"error\"]\n",
    "model.fit(X_train,Y_train, verbose=True, eval_metric=eval_metric, eval_set=eval_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 285
    },
    "colab_type": "code",
    "id": "lc79U4_v5E7D",
    "outputId": "d17e690e-2937-476d-fbbd-3f8e2a101f8a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff8c5ee6780>]"
      ]
     },
     "execution_count": 48,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FF1/k888/55VXXqG1tZWrrrqK888/n+zsw488ORHynHb++U4lAD+6YSYpditn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\niCgk4S+EEFFIwl8IIaKQhL8QQkSh/w+DpXVuUm+tkwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "error_train = model.evals_result()['validation_0']['error']\n",
    "error_test =  model.evals_result()['validation_1']['error']\n",
    "plt.plot(range(len(error_train)), error_train)\n",
    "plt.plot(range(len(error_test)), error_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 653
    },
    "colab_type": "code",
    "id": "_jbo3pleHjGR",
    "outputId": "e011a68b-300b-42f2-c35e-6f6fdf52afed"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.9\n"
     ]
    },
    {
     "data": {
      "image/png": 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Mo8v7VNARERERkSOlbctFeqfW1lZK9++ndO8eaoryaSorwFJbgm9jOXZXJX6WFryBfgfO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\nq1+zrMdsNjOqz+s87NvcMq1OAy86dGvOxwu3WH2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D0LVrV/bu3Uvbtm1JT0+3YTIRsQeG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\nex4XEWAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.84      1.00      0.91     10510\n",
      "         1.0       1.00      0.81      0.89     10799\n",
      "\n",
      "    accuracy                           0.90     21309\n",
      "   macro avg       0.92      0.90      0.90     21309\n",
      "weighted avg       0.92      0.90      0.90     21309\n",
      "\n",
      "{'base_score': 0.5, 'booster': 'gbtree', 'colsample_bylevel': 1, 'colsample_bynode': 1, 'colsample_bytree': 0.6, 'gamma': 5, 'learning_rate': 0.01, 'max_delta_step': 0, 'max_depth': 7, 'min_child_weight': 1, 'missing': None, 'n_estimators': 100, 'nthread': 1, 'objective': 'binary:logistic', 'reg_alpha': 0, 'reg_lambda': 1, 'scale_pos_weight': 1, 'seed': 0, 'subsample': 0.8, 'verbosity': 1, 'scoring': 'f1'}\n",
      "[0.00345526 0.02254158 0.00285168 0.00539803 0.00199984 0.0054052\n",
      " 0.15362307 0.00231655 0.005042   0.00213726 0.00403131 0.00203472\n",
      " 0.04848142 0.         0.00628464 0.07857612 0.02342204 0.03331334\n",
      " 0.48524153 0.05017592 0.03575169 0.02791681]\n",
      "Precision = 0.9173105903165846\n",
      "Recall = 0.9038260493690213\n",
      "Accuracy = 0.9025294476512272\n",
      "[[10504     6]\n",
      " [ 2071  8728]]\n"
     ]
    }
   ],
   "source": [
    "predictions = model.predict(X_test)\n",
    "model_performance(pd.Series(Y_test), pd.Series(predictions))\n",
    "print(metrics.classification_report(Y_test,predictions))\n",
    "print(model.get_xgb_params())\n",
    "print(model.feature_importances_)\n",
    "print(\"Precision = {}\".format(precision_score(Y_test, predictions, average='macro')))\n",
    "print(\"Recall = {}\".format(recall_score(Y_test, predictions, average='macro')))\n",
    "print(\"Accuracy = {}\".format(accuracy_score(Y_test, predictions)))\n",
    "print(metrics.confusion_matrix(Y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 659
    },
    "colab_type": "code",
    "id": "2FeuVxWCk_HI",
    "outputId": "9a1cdbfa-8cd8-429b-a294-efb745b3eba0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "term_ 36 months                        0.485242\n",
      "inq_last_6mths                         0.153623\n",
      "verification_status_Not Verified       0.078576\n",
      "emp_length_beginner                    0.050176\n",
      "home_ownership_MORTGAGE                0.048481\n",
      "emp_length_experienced                 0.035752\n",
      "verification_status_Verified           0.033313\n",
      "emp_length_intermediate                0.027917\n",
      "verification_status_Source Verified    0.023422\n",
      "int_rate                               0.022542\n",
      "home_ownership_OWN                     0.006285\n",
      "delinq_2yrs                            0.005405\n",
      "annual_inc                             0.005398\n",
      "pub_rec                                0.005042\n",
      "revol_util                             0.004031\n",
      "loan_amnt                              0.003455\n",
      "installment                            0.002852\n",
      "open_acc                               0.002317\n",
      "revol_bal                              0.002137\n",
      "total_acc                              0.002035\n",
      "dti                                    0.002000\n",
      "home_ownership_OTHER                   0.000000\n",
      "dtype: float32\n"
     ]
    },
    {
     "data": {
      "image/png": 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v/sgxT09PPvroI6ZOnYpa/eBH3dLS0jh37hxr1qypdBtarZaFCxcq20ePHsXCwoJt27ZV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\nRETE6fwXyH6ckpQ1nJkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "coefficients = model.feature_importances_\n",
    "feature_importance = pd.Series(coefficients,\n",
    "                            index=features_corr.columns, )\n",
    "\n",
    "feature_importance_ordered = feature_importance.abs().sort_values(ascending=False)\n",
    "print(feature_importance_ordered )\n",
    "feature_importance_ordered[0:10].sort_values().plot.barh()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "DqIrOyklskhv"
   },
   "source": [
    "# MAX VOTING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "l5dzJri2L7fu"
   },
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "tOSY12HhN2mg",
    "outputId": "99005c71-9d49-49d5-97a6-ce06e84f7dcf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Duration: 2 seconds\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "model1 = DecisionTreeClassifier()\n",
    "model2 = KNeighborsClassifier()\n",
    "model3= LogisticRegression(class_weight='balanced')\n",
    "\n",
    "model1.fit(X_train,Y_train)\n",
    "model2.fit(X_train,Y_train)\n",
    "model3.fit(X_train,Y_train)\n",
    "\n",
    "pred1=model1.predict(X_test)\n",
    "pred2=model2.predict(X_test)\n",
    "pred3=model3.predict(X_test)\n",
    "\n",
    "print(f'\\nDuration: {time.time() - start_time:.0f} seconds') # print the time elapsed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "QfUwvd3lQQBa"
   },
   "source": [
    "# DECISION TREE CLASSIFIER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 310
    },
    "colab_type": "code",
    "id": "DFqXxNN8MYXo",
    "outputId": "77546ecc-7170-4958-c890-a8c89b32f2d7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.85\n"
     ]
    },
    {
     "data": {
      "image/png": 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9hwA4+5xTeebptVSUV7F/fzZr3/iAqqqG8yKVl1eSPOsv3HLrlQQHB7b1ZbQ/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\nClElzQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model_performance(pd.Series(Y_test), pd.Series(pred1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "-338ixjpQYr_"
   },
   "source": [
    "# K-NEIGHBOURS CLASSIFIER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 310
    },
    "colab_type": "code",
    "id": "pqXml6g9Mc3W",
    "outputId": "d948a6fc-d132-4ac7-e9e7-d1b7ffd420ae"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.75\n"
     ]
    },
    {
     "data": {
      "image/png": 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IKOCkoF9vxqa9rGJOK9EIHRERaTV1dXX07NnziDbPDjrsuqy6npzSwzidzoa2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\nOiIiIiIiIiIiDkaBjoiIiIiIiIiIg/kbUT6rMPNB/T0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model_performance(pd.Series(Y_test), pd.Series(pred2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "yfneiZoDQkWf"
   },
   "source": [
    "# LOGISTIC REGRESSION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 310
    },
    "colab_type": "code",
    "id": "K8xHVgJKMeRa",
    "outputId": "9b1e29bb-df0f-483f-8645-ba39fb0645f1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.61\n"
     ]
    },
    {
     "data": {
      "image/png": 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gwbURNO1/IwD2wkK2v/kOp48dx8Pbm4ZdOtFs0ABDXmNl41C3NxGpAGdajn+K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\nERGZYP4FWbinpKp0XssAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model_performance(pd.Series(Y_test), pd.Series(pred3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "30pz9XZ0OVi-"
   },
   "outputs": [],
   "source": [
    "import statistics as s\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ly3gQtMRQ0y-"
   },
   "source": [
    "# MAX VOTING ENSEMBLING TECHNIQUE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-VMI__zkOlIF"
   },
   "outputs": [],
   "source": [
    "final_pred = np.array([])\n",
    "for i in range(0,len(X_test)):\n",
    "    final_pred = np.append(final_pred, s.mode([pred1[i], pred2[i], pred3[i]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 327
    },
    "colab_type": "code",
    "id": "fu5P0byoOu1m",
    "outputId": "c68744c2-4210-4ec2-b887-f27e854956b4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.81\n"
     ]
    },
    {
     "data": {
      "image/png": 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wktPjPG5c8raKOc1EBR0REWk21dXVdOnS5Zhznp5te6eDEZeezntfZhxzbtve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      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall = 0.8096786413514518\n"
     ]
    }
   ],
   "source": [
    "model_performance(pd.Series(Y_test), pd.Series(final_pred))\n",
    "print(\"Recall = {}\".format(recall_score(Y_test, final_pred, average='macro')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 327
    },
    "colab_type": "code",
    "id": "d2fOS3teO-YP",
    "outputId": "89af9afa-9608-4919-dfad-62da76bfe0d6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Area Under the Curve: 0.81\n"
     ]
    },
    {
     "data": {
      "image/png": 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cdW5ntm3Zw5ndOpC2J50Bg3sTEn6sOfag2It46em1HErLIie7gPzcIqbcOB+A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\nrkJggg==\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall = 0.8081626474735256\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import VotingClassifier\n",
    "model_vc = VotingClassifier(estimators=[('lr', model3), ('dt', model1), ('knn',model2 )], voting='hard')\n",
    "model_vc.fit(X_train,Y_train)\n",
    "pred_vc=model_vc.predict(X_test)\n",
    "model_performance(pd.Series(Y_test), pd.Series(pred_vc))\n",
    "print(\"Recall = {}\".format(recall_score(Y_test, pred_vc, average='macro')))"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "credit_risk_analysis_ML.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}