Flipr Hackathon Main Model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "r7jwaksQZWc6"
   },
   "outputs": [],
   "source": [
    "!pip install missingno\n",
    "!pip install tensorflow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IMPORTING REQUIRED LIBRARIES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "n7GpjbvWZEZj"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.experimental import enable_iterative_imputer\n",
    "from sklearn.impute import IterativeImputer\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.decomposition import PCA\n",
    "from mlxtend.plotting import plot_pca_correlation_graph\n",
    "\n",
    "import missingno as msno"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 402
    },
    "colab_type": "code",
    "id": "iBY87BQnZEZs",
    "outputId": "127c7a81-2f3a-4828-d24b-e238c3347f39"
   },
   "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>Population_2011</th>\n",
       "      <th>Population_2001</th>\n",
       "      <th>Sex Ratio</th>\n",
       "      <th>Median Age</th>\n",
       "      <th>Avg Temp</th>\n",
       "      <th>Toilets</th>\n",
       "      <th>Water Purity</th>\n",
       "      <th>H index</th>\n",
       "      <th>Female Pop</th>\n",
       "      <th>Hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12442373.0</td>\n",
       "      <td>11978450.0</td>\n",
       "      <td>878.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.700440</td>\n",
       "      <td>10924403.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>4408916.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11007835.0</td>\n",
       "      <td>9879172.0</td>\n",
       "      <td>858.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>0.920018</td>\n",
       "      <td>9444722.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>2379169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8436675.0</td>\n",
       "      <td>4301326.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>0.097085</td>\n",
       "      <td>7896728.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>636502.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6809970.0</td>\n",
       "      <td>3637483.0</td>\n",
       "      <td>930.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>0.827744</td>\n",
       "      <td>6333272.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>126078.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5570585.0</td>\n",
       "      <td>3520085.0</td>\n",
       "      <td>852.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>227.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>0.847941</td>\n",
       "      <td>4746138.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>284973.0</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>782</th>\n",
       "      <td>36954.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>846.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>0.035280</td>\n",
       "      <td>31263.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>284973.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>783</th>\n",
       "      <td>36947.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>945.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>0.056394</td>\n",
       "      <td>34915.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1489500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>784</th>\n",
       "      <td>36828.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1019.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>0.066752</td>\n",
       "      <td>37528.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>106153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>785</th>\n",
       "      <td>36805.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>900.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>0.627556</td>\n",
       "      <td>33125.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>24720.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>36776.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>889.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>0.313383</td>\n",
       "      <td>32694.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3104060.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>787 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Population_2011  Population_2001  Sex Ratio  Median Age  Avg Temp  \\\n",
       "0         12442373.0       11978450.0      878.0        23.0      32.0   \n",
       "1         11007835.0        9879172.0      858.0        27.0      30.0   \n",
       "2          8436675.0        4301326.0      936.0        28.0      37.0   \n",
       "3          6809970.0        3637483.0      930.0        23.0      31.0   \n",
       "4          5570585.0        3520085.0      852.0        29.0      25.0   \n",
       "..               ...              ...        ...         ...       ...   \n",
       "782          36954.0              NaN      846.0        23.0      28.0   \n",
       "783          36947.0              NaN      945.0        23.0      36.0   \n",
       "784          36828.0              NaN     1019.0        28.0      28.0   \n",
       "785          36805.0              NaN      900.0        24.0       6.0   \n",
       "786          36776.0              NaN      889.0        25.0      37.0   \n",
       "\n",
       "     Toilets  Water Purity   H index  Female Pop  Hospitals  Foreign Visitors  \n",
       "0      219.0         150.0  0.700440  10924403.0      159.0         4408916.0  \n",
       "1      215.0         196.0  0.920018   9444722.0      148.0         2379169.0  \n",
       "2      212.0         102.0  0.097085   7896728.0      123.0          636502.0  \n",
       "3      217.0         118.0  0.827744   6333272.0      110.0          126078.0  \n",
       "4      227.0         109.0  0.847941   4746138.0       73.0          284973.0  \n",
       "..       ...           ...       ...         ...        ...               ...  \n",
       "782     68.0         103.0  0.035280     31263.0       19.0          284973.0  \n",
       "783     62.0         136.0  0.056394     34915.0       22.0         1489500.0  \n",
       "784     98.0         138.0  0.066752     37528.0       27.0          106153.0  \n",
       "785     63.0         145.0  0.627556     33125.0       15.0           24720.0  \n",
       "786     51.0         181.0  0.313383     32694.0       30.0         3104060.0  \n",
       "\n",
       "[787 rows x 11 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset=pd.read_excel('Train_dataset.xlsx')#encoding='unicode_escape')\n",
    "df_cat = pd.read_excel('Train_dataset.xlsx')\n",
    "X=dataset.iloc[0:787,[3,4,5,6,7,9,10,11,12,13,14]].values\n",
    "features=['Population_2011','Population_2001','Sex Ratio','Median Age','Avg Temp','Toilets','Water Purity','H index','Female Pop','Hospitals','Foreign Visitors']\n",
    "df=pd.DataFrame(X,columns=features)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 238
    },
    "colab_type": "code",
    "id": "lrS4f4UoZEZ6",
    "outputId": "b0734dbe-b386-4714-a2be-58fbc2ac12ce"
   },
   "source": [
    "# HANDLING MISSING VALUES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "nKLUAhjPZEZ_"
   },
   "outputs": [],
   "source": [
    "def missing_values_plot(df):\n",
    "    \n",
    "    missingdata_df=df.columns[df.isnull().any()].tolist()\n",
    "    msno.matrix(df[missingdata_df])\n",
    "    return missingdata_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 532
    },
    "colab_type": "code",
    "id": "e6ach5G8ZEaF",
    "outputId": "bab40901-92a0-40b8-fc45-314a3e5246e3"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "missingdata_df=missing_values_plot(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 738
    },
    "colab_type": "code",
    "id": "QC93Q5-RZEaK",
    "outputId": "05cd6f6b-58e9-4823-de41-fa1cde1d4bca"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x14046700d08>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABxIAAAR5CAYAAADpiUBeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nOzdebSlV1kn4N+bVDAJBGQIEATCpEzKPIOEBqQVBIQGRCWRQaQFVGgalG6lG9FWlEGGZlAQaUUbISCgjSiiCMgMCRBQggyBMGMgEELI8PYf33eLk7vrJlXFvffUufU8a2VV1TnfuWtXZa+999m/PVR3BwAAAAAAAGDRIcsuAAAAAAAAAHDgESQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCwBJVlb4YAAB2CON7ANgzfeTq8j8OAJagqr4nSbr7gqqqZZcHAADYf8b3bDX1ClhV+sjVJ0hkx9AIsVmq6tJV9fCqOmzZZWFnqqpLJjm1qp6XJN3dSy4SO1xVHbrsMrBzqV9sNuN6tov2i81ifM9Wm+vYf6uqey+7LBwcjMfYLPrInWHXsgsA+6qqjkxyfJJrJPlskpO7+5+6u6vqkO6+YKkFZKVV1VFJPprkX5K8LMm5yy0RO01VXTrJu5NcNcmtq+rY7v7UkovFDjEP0B+V5NpJvpTkg9398u4+f7klYyeY69fjk1wryReTfKC7/4/6xWaYVylfr7tPnsf1ZZKBzaJ/ZCsZ37PV5nmKtyf5cpIvVNWu7j5vycVih6iqI5LcL8kNk3wlydu6+5+Nx9gM+sido7QFrJJ58PSOJIcnuSDJ1ZKcleQvuvsXllk2Vt/cuZ2c5NQkD+nu0/fwjEEU+22uYycl+VCSVyV5UZJHdPeLl1owdoS5j3xXphMnvprkmkkun+S1SR7Z3Z9bYvFYcVV1qSTvybTA5vOZ6tcxSd6S5OHd/eklFo8VN4c8705yRpL/0t3vnF837uK7pn9kKxnfs9Wq6vAkf59p7usxST66PkTUX7K/5j7yb5N8b5IjM82zfiTJk7r7xGWWjdWnj9xZHG3KyqiqXUlenmkF/N27+/uT3DzJe5M8oqpeMTdQLm5lny2E1KcmOSHTJGmq6rCqOnKuf1nb+bq8krKq5vbpfUk+keQXkrw+yTuTPK6qrr7MsrH65qPZ/jhTH3mP7r51kpsl+cMk907yJ1X1Q8srIatsPtbodzLt4rl7d/9Ikltmmsz6oSSvqaqbLLGIrLCqukSmturqSW6c5Her6lbJ7nGXY7XYb/pHtpLxPdvkZkkumeQpmUPEqrp2Vd24qu48n8wlRGSfzTsR35jk60kemGmhzc0zhYoPW2LR2AH0kTuPyXBWyWUzHUXzikxHT6a7T0nyyEzhz39K8pL5dRe3stfmYPCfklwvyXO7+/PdfX5V3TXJizOtkP/rqnpysrt+aT/Za/MA/eQkpyd5UHef3t1fSPLqTPXuh+bn3NPD/rpEkh/ItFr535Kkuz+TacLhzUnunOTpVXV0oq6xb+bJqeskOW1t52F3n5HkpUl+OslRSV5SVddM1C/22QOT/FiSpya5T6ZjtZ4mTGST6B/ZEsb3bKMbZzoF4q1ziHjfJG/I1Ia9Icnbq+pH5iPCYa/MY6tHJ6kkj5+Plr+gu9+f5ElJfrSqbrDUQrKy9JE7k4lwVsnlknx/kq/OEwq7qurQ7v5YplWmX01yj6p6fuLiVvbefK/m/0hyXpJfnlf33TPJX2eaOD0lyRWS/HpVvXLtMya12Ac3S/InSR647visZ2c64uFX5+No3NPDPpvbostlmij9+kIfech8RPOfZeojb53kD5JEXWNvzTvzD890rPyu+bVdc5v17UwLcR6WqZ/8w0T9Yp99PNMkw3O7+++S3D9TmPj0dWGi767sD/0jW+XGMb5ne3wu046xy8+Lnf88yYlJfi7JQ5NcKtNxgbdKnNDFXjsqybGZNmZ8ONn9vTKZNm90kksvp2jsAPrIHUjnwir5TKYt0L9UVdebz4Rfq8OHZ7r34g+T3LGqfmBJZWQFzZMJr810vNFxmQLEFyX5rSQ/0d0PyLRS/slJ7ltVv5IIq7l4VXVYknT325L81h7u4Dk/yV8luUWmXRgRULOvenJ6prbrsVV1s3V95KWSfCBTm3abqrrTckrKKllov87t7m9lOhHi/lV1p7V7eRbu43l7kv+e5LZV9UtLKzQrqbvfmuSm3X1GVe3q7n/I1CfeIMkzqupWc127YPFzJkq5OHO90T+yJbr7HUmeYnzPVlhXZ07LFPjcJ9P9dX+Rqe69srv/JMk9kpyTqS3L+v4SFi2M8c/M1D8+sbvPXXdE7icz3cl59AY/Q5vGRZr7yN/UR+4svnyxMrr7rExboK+d5Ler6oZJMt/J87j5vd9Ocq1MEw+wtzpJuvv1Se6Z7xx/9Pvd/cX5vS8meV6Sf820uwwuUlVdMslbqurnk6S7z1n/zLz66tlJvpbkvvNrAmou1nx36wnr7qV7RZJzk7y4qu6Q5LLzbp4nZ7qP4Dnzc9fe3tKyahbar4cvvPw3mQLD51XVTdfaqnmi/twkr03ykSQ33fYCs1I2aL/OS5K1kLq7/ynT5ML1kzwj0309qaprVdVj52dMlHKRFsZUJ0b/yCaoqkssHIO71v9diPE93421Ora2E38Od96X6RSuFyT5n0nO6e5vzM/v6u5PJnlWkhtV1Q8uqeisgIUx/iOSaQ6su0+bf784rjo3yWGZdvWvffbIqrrb/Kw2jYvV3d9ev/BPH7naBIkckKrqiKp6eFU9u6p+df7Cl+7+3Uxf9G6e5IOZJqzel+TV3f3C7v5sks8nufKyys6Bb65fPzXXrftn2nKfZHeYePskJ84rtHaveO/uLyX5UqYjRbSfbKimS6Xfk+l4mdvVbA/PHdrdn0/ywiQ/uTYwh4tSVUcleVuShyS5flXtSpLu/vPMK5EzHTf54STvSPKXSX6vu89O8pUkV932QrMy1rVft1/oA/8tyfMzHW/67Kq6yfyl79D5/a9mGpddc61Ownp7aL/W6tcwgTCHiffNdI/KM6vqPkmelunI02O3r9Ssiqr6nqq6S1U9qqruVlVXTZLuflmmBaeJ/pH9VFVHZqo/z6mq79vo/lbje/bXHurYBZkXPWcKEt+aaUfilarqmDlkPG9+/4JMx5/++zYXmxWxbox/2zmo3mgn2AVJvrnus7+f5IVVdcUtLywrZ/0869qCwflaqEMWntNHrjBf8jngzBMMb0xy2SSXSHL1JO+pqod19we7+zeq6u8yhT9XTfIv3f2n82dvleTbmc7zhsHCBNZlknxPkismOb2qXtjdv5kk3f32hecPXTuzu6quk+R7k7zGKng2Mg+yT8rUDv1NkkcleV53v2v9swvnwf9dkickuXuSv52/FKpjDGq6tPwfMy1q+O9JTl6YQEh3/1FVvSXJDyb5viSf6e6/nD97o0yLyD643eVmNWzUfmU6Pj7d/adV9b1JHpPk/1TVo7r7LfNnL5PkmPmz2i8GG7Rfw3Gla6/Nu33ePAeIJ2Y6yu2sJDfr7k9ta+E54M1j/Ndk+n54bKadFK+qqqd098nd/aKq+vskN4n+kf1zfKYJ+MsmeVJV/UZ3nz63VbsXQxjf813YYx1LpqsyqupZmeYw7p7pfsQXJflcVV0pyQ8n+UQWwh9Ysy9zFLPzMo25Dq/pKNRnJPmZJLdbO7UL1lzcPOti36ePXG2CRA4o8zb7tyb5YpJf6O73VdUdM006XC/zl7s56Hn74qC9qq6QqTM8L/NFwbBoHgD9ZaYJrAdlqid3TPLUJL8xH1PzuO4+r6oOzbRAfi1EvEqSJ2Y6I/6lyyg/B755gP7+TF/iHpJpIcTxSX65qn5+PqJ50N1vraoXJPnFqnqmCVIuwj0zhTRPSPLB7j6/qtZ24V+mu/+1u09Ncuq6PvLoJI/NNLH6zmUUnAPbxbVfSb7V3ed393Or6uuZxlxvrqo/SHJ2phDxFkl+yZdANnBR7deluvtj60LExXt6Ppbkuknu2N2nbHO5OcAt7OL5cpKHZ6ozd8k0yf6RJCcnSXd/IlMbt/hZ/SN7691JTk/ymST3T9Jz0PPZPSyCaON79sOGdSxJuvtVVXVmkkdnOpr5x6rqjEwT9zdPctx8QgTstp9zFBdk2tjxfUl+J8lPZwoR3789pWZV7OM86+6+Uh+5mhzNxwFjPgbrOUm+keSR8znwa8canZTk7Kq68rwSfs0h82fvl+QPMq1k+Ol5mzSsd0ySa2QKAj/U3ed195syDcT/PckvZlpplXmydO3L4MOSvDjTBNiPdffHllB2DnDzQogPJflUkuO7+3Pd/c4kb0hy10y7WXcflbvwubXjRP450xdHfTMX5eZJDuvuk+ZJ+Htl2oFxcqZQ50VVdUzynaMCq+r4JH+UqY+839rKZlizN+3XXN8OS5LufmmmiYgnJrldkuMyTWLdobst5mIjF9V+vXWD9usqmcZmN03yH4SIrDePq34903fIR3f3m7v7U939R5m+Hz5s3jG9p8/qH9krcz37Qqax+qMz1a0HZto1drX1IeLCeN/4nr1ycXVs7bnufmOSB2faHfaFTIsgPpop5PnANhebA9z+zlFkOlL3K0l+NdMCnR8WIrKBfZlnvaBm82f1kSvG/ygOJIdmWnn16iQfX3uxprstjknylEyrS99YVY9NprBnDiDPzlSfj+vuk7e53KyOKyW5ZqajjC5YmBB9Z6ZO75tJHl1Vv772gaq6cZLbJKlM9euk7S82K+JHk/xDkp+ZVyavDY6eluSSmY5xW3+J+e7J0u5+RZJbzqvlYSNfz/SlLlV17ySvyrTC9BmZjv17YJKXVtXlFj7z0UxH09xJH8kG9rb9Ore+c6fdKd391CR3yBQQ/XR3f2j7i84K2Z/26xJJLp3kNiZI2cDlktwoyXsz7VxdnBA9OdMk6SU2+Kz+kb3S3RfMQfOZSe7b3b+aqd36ySRPrKqjq+pxmY7O3T3eN75nb+1lHXt8TfeOfa2nu9Ef2N13y3QaxEeWV3oOYPs1R5Hk/Ey7/M/MFFK/d5vKy+q5cvZhnnXesW8ObEVVj/faw7aaV8g8tLufM6+0+mJ3nzO/d4kkH0hyTpI/zdSRHZ9pgP6L3f2yhZ9zRHefve1/AQ54a9vnq+rymVa8/FumOvf5qjq8u79VVb+fqfP7apLrJ7nP2qrkuV6e2d1fW9bfgQPX3IY9qLtfWFWX6O5vr3v/Mkn+b5IfSHKP7v6XdUe2XehOKFg0H9f2c9397PnPx2cakN8q0w6KKyZ5Qnd/s6oOn197WZI/6O5fXvg5Q92ETWq/1nZfXOh12MT26/Du/ta2/wU4oM0TVZefx/OPTPJX3X3aumO9j8t0B89NNtotrX9kT+b6dXTPR0oufJ98RpLrdPe95tf/d5KfSnJGprs5r5/k3+Znje/Z0HdRx26QqY6dbwzGRjZpjH/fJCd198cDCxbbr5ruR3x3pg1B+zLPqo9cQXYkslT1nQtZf7Oqrtvdn+7ucxZWkf5SppWl90ry9O5+SZJfzrSi4TaLP0uIyHpVdci84urKSdLdX8m0+v1WSX6rqq4wd243zHRZ+auSPDtTUH2NtZ8z10shIoOFNuz3qup63f3thVV+SZK57vyvTHcR/Mf5tV73jAEUg7l+/XOmuwVuOL/8N0nek2mF8oOTfKG7v5kk80T7/8v0pfDOVXWFhd1jJkm5kE1sv3pPr3Nw24T26/IL3wfO2c6yc+Crqktluo/n8VV1ze5+3voQcXZWkl2ZdrWuffaIqvrBtT/rH1lvoX49Zq39WhirvzLJdarq2Pn1R2U6uu1qmY4KPHsOg8r4no18l3Xsm4sh4vyMMRi7fbdj/LVnu/tVQkTWW9d+3aC7v57kdUlukX2bZ9VHriBBIktT04W/JyU5KtNxMw9Ye2+hQXlupqOyPtXfOR7kg0k+nzkcgj2ZO7fnJnlHkg9X1Uuq6trd/cQkL8903+FpVfX+JB9M8prufmlPRzZ8OdOACja0rg07LMn9k/GL3DwQPznJG5P8l6q6zjYXlRW0rn59T5L7Jkl3fynTna2VaULh0Pn5XfP738q0YvmQJN8wQGdPtF9spU1qv85aGPubIGW3eYz/7iSXSvLOJJ9de28PdaWTnDv/t1Y3n5nkGfPv4ULW1a/3JDl13SNfyzQPccn5+T/LdHzu3ya5ZZLfqapjtFtsRB1jK23GGF/dYiN7aL8+kSTd/fgkJ2baBGSedQcTJLIUc+d2cqZG58czraz6+YUVy2tHZX2ru89c99kbZpqAePM2FpkVMndu78p07Mc7k7woyf2SPD/ZvarvZ5P8bqaVWj/f3T8zf/a4JN/KdPwp7NHetGFrenJmppVYV8u0UitVdej2lZhVchH160ZJ0t0vTPLHmXbnP7aqfrS7z5s/e3SSayf5SKa+Ei5E+8VW0n6xleZdqs9L8oUkJyQ5cT7NptY9t2v+7VqIeGRNx+c+LclDk/zK+u+YsEH9utBOnu4+Jcn7ktyxqv4i006e+3T3j2fadX377S85q0IdYysZ47OVNmi/zq7pSrJ09y8kuU+mu8/Ns+5Quy7+Edhcc+f2gUxHlh7f3Z+rqpdnWrlwuySnVNWh3X3+/Pzuc5Or6oqZjjY9PNPWabiQuRP7kySnJ3l4d39yfv1tSV5ZVQ/p7pd09+uTvL6qdi1MYF0+ycMynd/tsl/2aD/asJoH6n9YVQ9K8qSqOrG7z13aX4ID1sXUr1vP76W7n1xVZ2TqE19TVS/KdPzfNZIcl+QO7chv1tF+sZW0X2yDI5J8f5KXdfenkqSqbp/kLlV1hSSnJfn9tbF9pnp1eKYV8PdL8qAkt+7u9297yVkFF1e/Pp1pgvRjmSZTP5fkgZlOwEl3n1BVV+7uzy+j8KwEdYwtYYzPNrio9uvKSf4lyfO6+61VddhaXTLPurOUHctsp3kFw5uSnJe5c1t4742ZLo+++Z5WiFbVPTN9+btrkjt398nbU2pWSVXdLclvJ3lqklf2fEdFku/LdFfPX3T3f611F/tW1f0yTTDcNcld1C/2ZH/bsLWBelU9NclDktzIF0DW25/6VVW3SvKTmVadnpvpy+OvdfeHtrPsHPi0X2wl7RfboaqukulIrUd292uq6gFJXprkX5NcMckVknw4yb16ujPxBkn+Psk3khyT5I7d/b7llJ4D3V7Urytl2mXx2EyTom9I8rr5++buCXrYiDrGVjDGZzvsRft1dKYx2D3nMdghma43MM+6gzjalG01BzcPSfJTa53bwjEOr8u0Evk/rXs9VXWfJL+Y6az4O2p8uAifSnJmktf3dy667+7+TKZt9Ndd/4GqOizJkZkmH45Tv9jI/rZh/Z1VO7+V5JYG6OzJPtavtTvF3tXdj0tyhyQ3zXSvsEl4BtovtpL2i21ydqZ7D28yj99/L9MCwv+Y5JqZJt4vneQv5/r31Uwr6C+X5LZCRC7GxdWvB2eakH9+ksd192v6O3e5CnjYG+oYm84Yn21yce3XQzPdzfnqeR72gphn3XHsSOSAUVVHZNqK/6nuvuse3r9lkk9095e3vXCslKo6sru/ubbrcOHX1yU5pLvvsfDs4tG5R3X315dWcFbantqwtSB7/r1VpOy3DerXYvtVbVDHftJ+sZW0X2ymqvqdTIHhM5LcO8mDuvtj83uXzHQM4POSPLi7/7yqnpTk5d39r8sqM6tjL+rXTyX530ke2t0vW1pBWVnqGNvJGJ/NtA9jsN3tl3nWncWORA4Ic+d1dpJnJTluPqN77b1DkqS73y1EZG909zfnX9eOLl1r676Z5LC156rqUkkeV1U/MT+vc2O/bNSGLU6MGqCzvy6ifu0+ntkkPPtL+8VW0n6xBV6Y5Ev5zmk1ZyTTPendfVaSEzMdlXtsknT3bwgR2QcXV79emal+XWVpJWTVqWNsC2N8tsDejsF2t1/mWXcWQSIHhIXO601JvpLkHsnulTIXbPhB2Avdfd78228luUxV7aqqo5I8M9NW/FOWVjh2hItqw5ZWKHYM9YutpH6xldQvNlt3fyLJCZmOML16prt30t3fnh+5cpJPJzktUdfYN/tQv05fSgFZeeoY28UYjM2m/UKQyAGluz+c5LlJfrKqbmuFMpthYaB0bpJdSS6V5GmZtt3fqrtPXVbZ2Fm0YWwl9YutpH6xldQvNlN3vyfJHZN8Lcnzq+qxVXVsVd00yeOTXCbJ2+Zn1TX2yb7UL9gf6hjbyRiMzaT9Ori5I5EDTlXdOMl7k/xxkkfYas93a+GOxOcmuVWSDyd5QJLbd/f7l1s6dhptGFtJ/WIrqV9sJfWLzVZV1820OPDHkpyVaVLr/CT36e6Tllk2Vp/6xVZTx9guxmBsNu3XwUmQyAGpqp6T5AXd7chJNk1VPTnJr2fq4O4sRGSraMPYSuoXW0n9YiupX2y2qjoiyY2S3DzJZ5K8r7s/s9xSsVOoX2w1dYztYgzGZtN+HXwEiRxQ5jsRVUq2RFXdJMkbktypuz+y7PKw82jD2ErqF1tJ/WIrqV8AANvPGAzYLIJE4KBSVUd099nLLgcAAAAAABzoBIkAAAAAAADA4JBlFwAAAAAAAAA48AgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGOxadgF2gF52AQAAAAAAAFiKWnYBtpIdiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkLigqq5dVW+tqo9W1fur6hbLLhMAAAAAAAAsgyDxwl6Q5I+7+weSPCHJy6qqllwmAAAAAAAAVlRV/WNV9Qb//c3CczesqldV1Wer6qyqOqWqHldVuxaeefBF/KyuqitvZtl3XfwjB66qumqSX0lyiyQ3TnJEkmt29yf38OzVkjwzyY8kqSRvTPKY7j5tfv/oJLdJcvck6e6/mzPEmyd5z1b/XQAAAAAAANiRHpnk0uteu22SZyR5bZJU1VWS/GOS05M8JsmXk9wlye8luWKmPCxJ/nr+7KJK8rokH+/uz29mwVc6SExynSQPSPLeJG9Jcrc9PVRVRyZ5U5Jzkvxskk7ym0n+oapu1N1nJbl6ks9297kLH/3U/LogEQAAAAAAgH3W3R9e/1pVPTzJt5P83/mlH09yhSS37+6Pzq+9qaquneSEzEFid38pyZfW/awfTnL5JP9js8u+6kHiP3X3lZKkqn4uGwSJSR6e5FpJrtvdH5uf/0CSU5M8IlPiuyeONQUAAAAAAGDTVNURSe6f5HXd/e/zy5eYfz1z3eNfzcVfVfizuXAouWlW+o7E7r5gLx+9V5J3rIWI82c/keRtSe49v3RakqtU1WELnzt2fh0AAAAAAAA2w32THJXkpQuvvSLTcabPraprVtWlq+o+SY5P8vSNftBCKPlX3f2VzS7oSgeJ++CGST60h9dPSXKDZPdW0HcleXCSVNXaXYrv3Z4iAgAAAAAAcBA4IckXk7x+7YXu/kKmuw+vn+TjSb6W5MQkT+3u372In/UTme5ffOlFPLPfVv1o0711uSRn7OH1f09y2YU//+ckL62qxyf5ZpKf6e7ehvIBAAAAAACww1XVVZLcNcmzuvu8hdePTvKqJGcluV+SryS5c5Jfq6pzuvupG/zIn810Z+L/24ryHixBYpLsKRC80B2I3X1qktttT3EAAAAAAAA4yDwo04mh63cQPiHJNZIc291rm+P+saoOTfKUqnpxd3958QNVdUymUPI5i6HkZjpYjjY9I9OuxPUumz3vVAQAAAAAAIDNdkKSk7v75HWv/1CSjy2EiGveleSwJNfZw896UJJDs0XHmiYHT5B4SqZ7Ete7QZIPb3NZAAAAAAAAOMhU1S0y5VV7Cv4+n+Q6VXXZda/fev719D185oQkH+jukzavlBd2sASJr01ym6q61toLVXWNJLef3wMAAAAAAICtdEKS85L82R7ee0GSI5L8bVU9oKruUlVPSfJfk7y6uz+9+HBV3SzJD2YLdyMmSXXv6erA1VFV95t/e5ck/znJIzNdKvml7n7z/Mwlk5yc5Owkv5bpvsSnJDkqyY26+xvfRRFW+x8QAAAAAACA/VV79VDVYUk+m+Qd3X3PDZ65TZInJblpkksn+WSSP0/y9O4+e92zz8qUiV21u7+w36W/uHLvgCBxo7/Am7v7TgvPXT3JM5P8SKb/qX+f5DHd/cnvsgir/Q8IAAAAAADA/tqrIHFVrXyQeADwDwgAAAAAAHBw2tFB4sFyRyIAAAAAAACwDwSJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBg17ILAADr1Y6+nnjzdS+7BAAAAADATmRHIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMNi17AIAAAAAAMCBqGrZJVgt3csuAbDZ7EgEAAAAAAAABnYkAgDAJrFaed9YrQwAAAAHNkEiAHBQEfTsG0EPAAAAwMHL0aYAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwGDXsgsAAADAxatadglWS/eySwAAALD67EgEAAAAAAAABoJEAAAAAAAAYCBIBAAAAAAAAAaCRAAAAAAAAGAgSAQAAAAAAAAGgkQAAAAAAABgIEgEAAAAAAAABoJEAAAAAAAAYCBIBAAAAAAAAAaCRAAAAAAAAGLMsk4AACAASURBVGAgSAQAAAAAAAAGgkQAAAAAAABgIEgEAAAAAAAABoJEAAAAAAAAYCBIBAAAAAAAAAaCRAAAAAAAAGAgSAQAAAAAAAAGgkQAAAAAAABgIEgEAAAAAAAABoJEAAAAAAAAYCBIBAAAAAAAAAaCRAAAAAAAAGAgSAQAAAAAAAAGgkQAAAAAAABgIEgEAAAAAAAABoJEAAAAAAAAYLBr2QVga1QtuwSrp3vZJQAAAAAAADhw2JEIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBg17ILAAAAAAAAcLCpWnYJVkv3sktwcLIjEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAICBIBEAAAAAAAAYCBIBAAAAAACAgSARAAAAAAAAGAgSAQAAAAAAgIEgEQAAAAAAABgIEgEAAAAAAIDBrmUXAAAAAICdrWrZJVgt3csuAQDARJAIAAAAAKwsQfW+EVQDsC8cbQoAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBAkAgAAAAAAAAMBIkAAAAAAADAQJAIAAAAAAAADASJAAAAAAAAwECQCAAAAAAAAAwEiQAAAAAAAMBg17ILAAAAACxf1bJLsFq6l10CAADYenYkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAAAAA0EiAAAAAAAAMBAkAgAAAAAAAANBIgAAAAAAADAQJAIAAAAAAAADQSIAAAAAAAAwECQCAAAAAADw/9m7+5Bt77qO459vuWybSrNQq810KcqsdIaxpVY0H0dsBipWhJiM2RPlH0Gm0B9J2gP0jIJa/lOJDnVr6Oaa4aJMrETNNmGzwpsITa2wB0T264/zMu6uz3Xd93no5m631wtO7vs+zvM4jt91Xt/7+OfNeZxQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCExENm5hdm5qMzc+fMPOeeXg8AAAAAAADcE4TEdnOSy5Pcck8vBAAAAAAAAO4pm0LizFw+M7fMzGdn5j9m5q9n5vvvjoXNzPkz8zsz896Z+a+ZWTPziFO8/oKZuWZm/v1gbW+dmYdvPe9a631rrTu+lLUDAAAAAADAV7q9Q+LMXJ3k2iR/k+QHkzwvyVuSnHP3LC2PSvL8JJ9J8uenWds5Sd6d5LFJXpjkR5M8Osmfzcy5d9P6AAAAAAAA4CvGzFw4M2+YmWv2ef1eIfHgk4C/meTn1lovXWvdtNa6ca31K2ut60+x38Nm5ruPee7smXn2KU57y1rroWuty7MLlqdyVZILkzxnrfX2tda1Sa5I8i1Jrj7pnH87M/96zOOC05wDAAAAAAAA9jYzX3dwR83bZubWmbn0izzO78/MJ2bm74547lkz89GZuX1mfv5Ux1lrfWyt9eJ9z7vvJxJ/LMmdSV6774EPvDTJu2bmqSdvnJmzk1yf5A9m5gFH7bjWunPDea5I8ldrrdtP2v8fkvxFkitP2vbEtdY3HPP4+IbzAQAAAAAAwOn8VpIb1lqPTfL4JLee/OTMPGRmHnho26OOOM4bkzzr8MaZ+eokv5fk2UkuSvJDM3PRzHz7zFx/6PGQrYvfNyQ+JcltSV4wM3fMzOcPquZPnma/lyd5R5J3zMyTD36gs5P8SXZv1jPWWp/duugjPC5JFdgkH8nuTQMAAAAAAIAvm5l5UJLvSfKGJFlrfW6t9W+HXva9Sa6dma892OeqJL99+FhrrVuSfPqI03xXktsPPmn4uSRvSnLlWuvDa60fOPT4xNafYd+Q+E3ZfefgryV5dZJnJLkpye/OzM8ct9Na6/NJfjjJjUneOTOXJbkuyROSXLbW+tDWBR/jwdl9l+Jhn05y3pYDzcwrZuZEkkuTvH5mTszMw+6CNQIAAAAAAHDfcWGST2Z3h84PzMzrZ+bck1+w1npLkhuSvGlmfiS7u4Q+f8M5vjnJyXfdPHGw7Ugz8/Uz89okF8/My0538H1D4lcleWCSq9dar1trvXut9ePZ/WAvm5k5bseDmPiCJH968PjOJE9fa31wz3Pvax2x7dh1HXuQtV651jp/rXX/g1uenr/W+pe7YH0AAAAAAADcd9wvyROTvGatdXGS/0xS32G41vrVJP+T5DVJrth4N8+jWthRzewL5/rUWusla61vXWu96nQH3zckfurgz5sObX9Xkocm+cbT7H+/JA/I7nsWz0pyzp7n3ddnsvtU4mHn5ehPKgIAAAAAAMDd6USSE2ut9x38+5rswuL/MzNPTfJtSd6W5Be/iHNccNK/z0/yz9uXerR9Q+JHjtn+hcp553E7HtzT9e3ZvTGXZPepxHfOzKX7LnLP9T3uiO0XJfn7u/A8AAAAAAAAcFoHd7z8+Mw85mDTZTnUrWbm4iSvS3JlkhclefDMvHLDad6f5NEz88iZ+Zrs7hJ63Ze8+AP7hsS3Hfz5zEPbn5ldST3y1p8zc/8kb03ypCRPW2u9P7v7ut6c5IaZuWT7ko90XZJLZubCk879iCRPzl34ZgEAAAAAAMAGP53kD2fmQ0mekOSXDz1/TpLnrbXuWGvdmeSFSf7p8EFm5o+TvDfJY2bmxMy8OPm/rxj8qSQ3Jrk1yZvXWsd9QHCzWevY26SevLjJLv49PsnLk3wsyXOTXJXkRWutNx6z369nV0+fttb6wEnbz0ry5iRPSfLI4+71OjPPPfjrZUlekuQnsvtSyk+utd5z0uvOTfLBJP+d5BXZ3fv1l7L7Xsfv2Hgv2a1O/wbeA47/1kqOs8d/BeDLxDVsG9evbczXNuZrG/O1jfnaxnxtY762M2PbmLFtzNc25msb87WN+drGfG1jvrYxX9ucwfN1r/5N7hUSk2RmHpTkVdkFxPOS3Jbk1WutPzrFPuclOX+t9eEjnjsryZPWWn95iv2PW9x71lrfd+i1D0/yG0ment0v7eYkP7vW+sdT/Fh3hTNydF2AtjuDL0Jwn+Mato3r1zbmaxvztY352sZ8bWO+tjFf25mxbczYNuZrG/O1jfnaxnxtY762MV/bmK9tzuD5ulf/JvcOiRzrjHwDXYC2818BzhyuYdu4fm1jvrYxX9uYr23M1zbmaxvztZ0Z28aMbWO+tjFf25ivbczXNuZrG/O1jfna5gyer3v1b3Lf70gEAAAAAAAA7kOERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAy2topAAAIABJREFUAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAAAACKkAgAAAAAAAAUIREAAAAAAAAoQiIAAAAAAABQhEQAAAAAAACgCIkAAAAAAABAERIBAAAAAACAIiQCAAAAAAAARUgEAAAAAAAAipAIAAAAAAAAFCERAAAAAAAAKEIiAAAAAAAAUIREAAAAAAAAoAiJAAAAAAAAQBESAQAAAAAAgCIkAgAAAAAAAEVIBAAAAAAAAIqQCAAAAAAAABQhEQAAAAAAAChCIgAAAAAAAFCERAAAAAAAAKAIiQAAAAAAAEAREgEAAAAAAIAiJAIAAAAAAABFSAQAAAAA4H/Zu/N4zcfygeOfyxgMQ5Sf+pVUKBKVsmRokeqXNQkpftmKVolIUpQlRdm3ytIvRdEmZUkbRVJZsqRISipb9m2Y6/fHdT/jmec5Z+Y8zMyZM/N5v17zmnO+z/d5zveM2/29v/d139clSVIfA4mSJEmSJEmSJEmS+hhIlCRJkiRJkiRJktTHQKIkSZIkSZIkSZKkPgYSJUmSJEmSJEmSJPUxkChJkiRJkiRJkiSpj4FESZIkSZIkSZIkSX0MJEqSJEmSJEmSJEnqYyBRkiRJkiRJkiRJUh8DiZIkSZIkSZIkSZL6GEiUJEmSJEmSJEmS1MdAoiRJkiRJkiRJkqQ+BhIlSZIkSZIkSZIk9TGQKEmSJEmSJEmSJKmPgURJkiRJkiRJkiRJfQwkSpIkSZIkSZIkSepjIFGSJEmSJEmSJElSHwOJkiRJkiRJkiRJkvoYSJQkSZIkSZIkSZLUx0CiJEmSJEmSJEmSpD4GEiVJkiRJkiRJkiT1MZAoSZIkSZIkSZIkqY+BREmSJEmSJEmSJEl9DCRKkiRJkiRJkiRJ6mMgUZIkSZIkSZIkSVIfA4mSJEmSJEmSJEmS+hhIlCRJkiRJkiRJktTHQKIkSZIkSZIkSZKkPgYSJUmSJEmSJEmSJPUxkChJkiRJkiRJkiSpj4FESZIkSZIkSZIkSX0MJEqSJEmSJEmSJEnqYyBRkiRJkiRJkiRJUh8DiZIkSZIkSZIkSZL6GEiUJEmSJEmSJEmS1MdAoiRJkiRJkiRJkqQ+BhIlSZIkSZIkSZIk9TGQKEmSJEmSJEmSJKmPgURJkiRJkiRJkiRJfQwkSpIkSZIkSZIkSepjIFGSJEmSJEmSJElSHwOJPSJi74i4PiKmRMSmo309kiRJkiRJkiRJ0mgwkNjvJ8AGwIWjfSGSJEmSJEmSJEnSaHlSgcSIODciMiIOmNkX1PUzlo6IoyLikoh4sP2850/n/OdGxJkRcU9E3BsR34mIZQb9uZl5aWbe+FSuXZIkSZIkSZIkSRrrBg4kRsQ7gJfNgmvptTywJfAf4KIZXNPCwE+BFYFtgf8FXgj8LCIWmcXXKUmSJEmSJEmSJM3xImLZiDgxIs4cyfkDBRIjYnHgMGC3EZ7/rIiYNMxrEyJi/em8/cLMfGZmbgCcMYMf9R5gWWDTzPxeZn4f2AR4HrBz18/8fUTcMcyf547kd5IkSZIkSZIkSZJGKiLGRcTlEXH2U/iMkyLitoi4eojX3hwR10fEDRGx1/Q+JzP/kpk7jvTnDroj8fPANZl52gjP/whwfkS8uvtgREwAzgZOjoiJQ70xM6cMcF2bAL/OzBu63n8T8CvgLV3HXpGZSw7z5+8D/DxJkiRJkiRJkiRpJD4MXDfUCxGxVEQs2nNs+SFOPQV48xDvHwccA6wPrAS8IyJWiohVIuLsnj9LDXrhIw4kRsQ6wLuA9w/w+Z8AfgT8KCLWbp8zAfgBlR71TZl5/wCfN5yXAH0RWOAa6h9NkiRJkiRJkiRJmq0iYmlgQ+Arw5zyWuD7EbFQO/89wJG9J2XmhcBdQ7x/DeCGttPwUeB04C2Z+YfM3Kjnz22DXv+IAokRMR44ATg0M68f6Ydn5mPAO4HzgHMiYj3gLODlwHqZedWgFzyMp1O1FHvdBSwxyAdFxD4RcQuwFvCViLglIp41E65RkiRJkiRJkiRJ85bDgT2BITNxZuYZwLnA6RGxNbADsOUAn/8coDvr5i3t2JAi4hkRcTywakR8fEYfPv8IL+JjwATgwBGeP1VmPhYRWwHfAi6gAn7rZeaVg37WjH7UEMdi4A/JPAA44KlfjiRJkiRJkiRJkuZVEbERcFtm/i4iXjfceZn5+Yg4HTgOWG7AbJ5DxcKGipl1ftadwHtH+uEz3JEYEctQKUo/CSwYEYtHxOLt5c7342bwMfMDE6lo63hg4ZFe4Aj9h9qV2GsJht6pKEmSJEmSJEmSJM1KawObRMRfqZSjr4+IU3tPiohXAysD3wX2HfBn3AI8t+v7pYFbn9TVDmEkqU2XBRYCTqWCcp0/AB9tX68y3JtbTtfvAa8AXkXtSjwnItZ68pfd5xqqTmKvlYBrZ+LPkSRJkiRJkiRJkmYoMz+emUtn5vOBrYCfZuY23edExKrAl4G3ANsDT4+IQTJnXga8MCJeEBELtJ9z1kz5BRhZIPEKYN0h/kAFF9cFbhjqjRGxIPAdYHXgDZl5GZXX9SfAuRHxqqd09U84C3hVRCzb9bOfT0V6Z9o/liRJkiRJkiRJkjQTLQxskZk3ZuYUYFvg5t6TIuI04BJghYi4JSJ2hCoxCHwQOA+4DvhWZl4zsy4uModNkzr9N0YkcGBm7jOdcw6loqdvyMzLu46Pp2omrgO8YLhcrxGxeftyPSpf6/uB24HbM/MXXectAlwJPATsQ+V+3R9YFHjpgLlkB/Xk/gFnsRi4OqSe5P8KkmYB+7DB2H8NxvY1GNvXYGxfg7F9Dcb2NRjb1+BsY4OxjQ3G9jUY29dgbF+DsX0NxvY1GNvXYGxfg5mD29dc/V9yVgcSlwCWzsw/DPHaeGD1zLx4Bj9jKL/IzNf1nLsMcBjwRuo/2k+AXTPzrzP4VZ6qObLp2gENbg7uhKR5jn3YYOy/BmP7GoztazC2r8HYvgZj+xqM7WtwtrHB2MYGY/sajO1rMLavwdi+BmP7GoztazC2r8HMwe1rrv4v+aQDiZpqjvwHtAManP8rSHMO+7DB2H8NxvY1GNvXYGxfg7F9Dcb2NRjb1+BsY4OxjQ3G9jUY29dgbF+DsX0NxvY1GNvXYGxfg5mD29dc/V9yJDUSJUmSJEmSJEmSJM1jDCRKkiRJkiRJkiRJ6mMgUZIkSZIkSZIkSVIfA4mSJEmSJEmSJEmS+hhIlCRJkiRJkiRJktTHQKIkSZIkSZIkSZKkPgYSJUmSJEmSJEmSJPUxkChJkiRJkiRJkiSpj4FESZIkSZIkSZIkSX0MJEqSJEmSJEmSJEnqYyBRkiRJkiRJkiRJUh8DiZIkSZIkSZIkSZL6GEiUJEmSJEmSJEmS1MdAoiRJkiRJkiRJkqQ+BhIlSZIkSZIkSZIk9TGQKEmSJEmSJEmSJKmPgURJkiRJkiRJkiRJfQwkSpIkSZIkSZIkSepjIFGSJEmSJEmSJElSHwOJkiRJkiRJkiRJkvoYSJQkSZIkSZIkSZLUx0CiJEmSJEmSJEmSpD4GEiVJkiRJkiRJkiT1MZAoSZIkSZIkSZIkqY+BREmSJEmSJEmSJEl9DCRKkiRJkiRJkiRJ6mMgUZIkSZIkSZIkSVIfA4mSJEmSJEmSJEmS+hhIlCRJkiRJkiRJktTHQKIkSZIkSZIkSZKkPgYSJUmSJEmSJEmSJPUxkChJkiRJkiRJkiSpj4FESZIkSZIkSZIkSX0MJEqSJEmSJEmSJEnqYyBRkiRJkiRJkiRJUh8DiZIkSZIkSZIkSZL6GEiUJEmSJEmSJEmS1MdAoiRJkiRJkiRJkqQ+BhIlSZIkSZIkSZIk9TGQKEmSJEmSJEmSJKmPgURJkiRJkiRJkiRJfQwkSpIkSZIkSZIkSepjIFGSJEmSJEmSJElSHwOJkiRJkiRJkiRJkvoYSJQkSZIkSZIkSZLUx0CiJEmSJEmSJEmSpD4GEiVJkiRJkiRJkiT1MZAoSZIkSZIkSZIkqY+BREmSJEmSJEmSJEl9DCRKkiRJkiRJkiRJ6mMgUZIkSZIkSZIkSVKf+Uf7AiSNTRGjfQVjS+ZoX4EkSZIkSZIkSYNxR6IkSZIkSZIkSZKkPgYSJUmSJEmSJEmSJPUxkChJkiRJkiRJkiSpj4FESZIkSZIkSZIkSX0MJEqSJEmSJEmSJEnqYyBRkiRJkiRJkiRJUh8DiZIkSZIkSZIkSZL6GEiUJEmSJEmSJEmS1MdAoiRJkiRJkiRJkqQ+BhIlSZIkSZIkSZIk9TGQKEmSJEmSJEmSJKmPgURJkiRJkiRJkiRJfQwkSpIkSZIkSZIkSepjIFGSJEmSJEmSJElSHwOJkiRJkiRJkiRJkvoYSJQkSZIkSZIkSZLUx0CiJEmSJEmSJEmSpD4GEiVJkiRJkiRJkiT1MZAoSZIkSZIkSZIkqY+BREmSJEmSJEmSJEl9DCRKkiRJkiRJkiRJ6mMgUZIkSZIkSZIkSVIfA4mSJEmSJEmSJEmS+hhIlCRJkiRJkiRJktTHQKIkSZIkSZIkSZKkPgYSJUmSJEmSJEmSJPUxkChJkiRJkiRJkiSpj4FESZIkSZIkSZIkSX0MJEqSJEmSJEmSJEnqYyBRkiRJkiRJkiRJUh8DiZIkSZIkSZIkSZL6GEiUJEmSJEmSJEmS1MdAoiRJkiRJkiRJkqQ+BhIlSZIkSZIkSZIk9TGQKEmSJEmSJEmSJKmPgURJkiRJkiRJkiRJfQwkSpIkSZIkSZIkSepjIFGSJEmSJEmSJElSHwOJkiRJkiRJkiRJkvoYSJQkSZIkSZIkSZLUx0CiJEmSJEmSJEmSpD4GEiVJkiRJkiRJkiT1MZAoSZIkSZIkSZIkqY+BREmSJEmSJEmSJEl9IjNH+xokSZIkSZIkSZIkzWHckShJkiRJkiRJkiSpj4FESZIkSZIkSZIkSX0MJEqSJEmSJEmSJEnqYyBRkiRJkiRJkiRJUh8DiZIkSZIkSZIkSZL6GEiUJEmSJEmSJEmS1MdAoiRJkiRJkiRJkqQ+BhIlSZIkSZI014mIGO1rkCRJGusMJEqSJEmSpoqI+Xq+dyJeM01EjOv53nkJzTS97Sszc7SuRZKkOYljfD0VDtj1pPnAp1nNG5pmld4JBmlms//SrGQfplkpIsZl5pT29doRsbgT8ZqZMvPxiFg4Ik6JiImd9ibNDJn5OEBEfDEiXjPa16O5i2MwSWNVRMyfmVMiYqGIeGMb8zvG14jNP9oXoLEnIl6emVe0zmc+H/w0s0XECzPzz5mZERHe2DQztcFSZ4LhPcBLgAWAqzPz2FG9OM0V2gD9sYiYH3gasDBwV2Y+0F63X9OT1unDImJhYBfg6cC9wNeBWzJz8qheoMa0nnvkl4CVgB9ExKGd49JMsjnwLuAk4EKfKzUzRcRywK7A+aN9LZp7dI3xFwRWBp4BXAo8kpkPj+7VaW7RNdYPcFe1Zo7Wrh6LiEWBHwCPA88ETh3dK9NY4o4yDSQiPg/8PCL+F6ATTBzly9JcJCIOBs6MiDdDDZrc2aOZpQVwOhOkZwIHAusCGwJHR8QPI2L50bxGjW1DDNB/AdxATcTvAD4M6qlpEwsTgcuB9wPvBPag2tpOEbHYaF6fxraue+Q3gfWAI4CvdwcRHZdpJvkucCuwLdRz5ehejuYWbSHXvcBdwLNG+XI0l2jPkZ0x/i+BnwDnAtcBh0TEM0f1AjVXaMHqzoLBjwKbuAtWT1VnHqw9Q/6aCiIeAHy797zRuD6NHQaANGIR8QFqVd/DwMcNJmpmi4hdgT2B5YC9IuKNYDBRT13var6I2B9YA9gSeAWwKrA9sDpwbEQsNEqXqjGuDdAXoVYnTwSOBT4C3AN8pfVz0sDaxGinPzsYuAX4H6r/Whm4ETgI2KZzrvRkRMRuwCRga+C7mXlLRCwSEUtHxDNdDKFB9Y7jI2J8Zt4HHAmsHxFrjM6VaW4wRE3ExzLzduBm4LVR5vN5Uk9W2zGdbXx1JhWo3ol6jrwA2Bj4ZkQsNYqXqTGuZ0HqRcBmwJI4d6+nqPVf8wFHAfcB2wE/z8yHIuI5EbGCpQw0EnZGGpGIWJGaTDgf2B14ANjHYKJmlohYFdgG+Ba18molYF+DiXoqOpPpQwyIJlGD819l5uOZeRdwGrW7Z11gn9l6oZrb7AY8BuwAHN9S5l7cXjPAoyelTSwsArwVWAj4dmZel5m3Z+bfM3NdapfinsCzR/NaNbYMEXheEbgsM38NTImIV1ITpRcCf46It7b3OfbXDHXSeUfEuIgYD9CVgvkXwCLUuMw2pSelayf1IRGxX0Ts3J4tHwEmZpnS+zzgs6VGqs13LUA9J44D9gXOzMwrqF3VxwEvAD7R0p5KM9TbB3XtRPwVcCc1N/G13rIF7lDUSHW3lZb54YXAOZn5d2BcRGwH/Iyaq7gmIjrjMe+PGpIDdY3UBOAh4IjM/DqVQut+DCZq5nkaNZHw5cw8HtgZeBH9wUTbmEYkIiYAl0XEhl3HxkXE4tTunXszc3LXpNaj1GKJC4FXtwl76clYBfhHq/U6JSK2Aj4HfCwzD42Ip0XE6qN8jRqbPkythN8eeLBzsNOPUatLnw68Y7ZfmcaUtjvnGW1n2GPt2JptwuER4HURsTlwGDW5cBtwDPBz4Pi2atlUlJqurl08CwC/AU5o7aoTYLyU6tN2j4hn2ab0ZEXEm4A3AztSY67vAq8C3hYRp0bE8RGxZURMioiXg6nmNTJtR+s4qg87FlgKuLQTXGzt6PPUItW34aJBjdwiMHVM1pnn2haYQgURr8rMR9v4bMeI2DMiJraAo/Nimq54otbm4hHxyai0pg8Db42I9wDfpOpUn00tRP0ncGhnAdjoXbnmZHY8GpHMvBx4V2b+uHUqP6d2XPQFE8HVCxpca1MbZuZPWhv7LpUupDeY6ASDRurFVO2KizoH2u7Du6mA4WYRsWxPMPFeagC1MDB5iM+UpjHM/W5+YLH2+hbAN4C9M/OQ1tZ2ArZoaWukQXyVSl8awJsj4hkwze6eR6gA48TRuTyNIZsBhwAvAYiIH1O1UhYBvkztbv0q8DLgo5n5lsz8AlUX6g5qkkvqE5UGtzOumtJ2V6xK1Q1+CfD1iDgf2CMqlfz3qV38r23vd45CA8vM8zNzFWr8/yLgvcB+VNt6CbAW8CWqD/t+RFg7USPSdrQ+TqViXo5akLpxe+3RrmDikVRGCBcLaoYiYgXg1oh4Y88c11JUOtO/AM+IiI9Tcxr7UuO0n0XEBOfFND1tTvXxtrj+Iirzw38Bn6bG8PsACwKvz8zdgFOAq4E7DSJqehyka4Y6k6SZ+Y/Oofb9LxgimNh28WwQEa8YhcvV2HZT+3s+gMz8HkMEEyNiYkS8zgdATU9m/p7aAXZvRBwZER/qevlsKlB4QkQ8rzMJHxHPBJYGrpn9V6yxpnunRUxbE+U6YLmI+CJwOrAXtVIZKm3zW4AHWn0oaUhDpS1qY7HjgCOALYCdImLJrlOWoh4O/zNbLlJj2U1UMPGYiPgFsAKwV2bem5lXUTt7XgpslZlHAUTEEu3YTcDjo3PZmpO158DtqDquHb8HNsvM/ag29z/UWP9DwB+BNYHnAW8HFw1qxnrvjz3B5wcz87bMPBf4HXA3sElmvoxaGPFS4HWZ+a/ZdsEac7oXCsYTpTJOAjZvh3eJiDXb8UdbG1yBqonuGEwj8QwqWPj9iFi3K8PbNVQNu6upHfsfo8pLvYYqAbQC9TwpDalrjmI+4FnUQvndMvOmzLyI2q3/KmCbzPx56+OeRy3E+dOoXbjGhDDQrKFExJKZecd0Xp+61TkiXgd8gVr9fiiwAFXA9a2Z+f3ZcLkagyJiHWrF3h3ATZl5U8/r3W3srcAJwPVUG3secDjwpsy8YLZeuMaEiFgwMx9pXz8HOAtYhgosntSO7we8m9rBsz+VXndNYANgUmZeOwqXrjGiDdCntF0Xv6dWuB+cmTdHxGJU+qMXASdn5o7tPS+l+rLHqEksJ+I1pK5UNAtRq97vAf6emde1158NfJxKe/Qd4MdUGvotgEWBV3bSVUrDaen9LqPug+/PzP9rx+frDeZExBrU4q7NgFdnpgtu1KcFeA4C3gP8EFgHuBHYMTNv7jpvYeC/gY9QgZ3VqNqv62fmebP7ujV2dO6P7etO+1kAuCYzD+o5d2ngBuAdmfndiJjfe6NmpNNOWn82HlgyM2/pzE9ExDbA/1G7fI4EzgXWoPq+x4DXuiBCIxERa1PtZhI1t/WzqDIsb6d2Uf8V+H7LENfJdLM/tTjCgI+GFVWr9TLgLuo5crNOStzu/qnNW6wOfIYah63Z+j/Tm2pIBhLVJyI+TQVqDszMP0/nvM7OxGxBocOB5al0bp/OzE/PjuvV2BMRRwObUsHnoHaG7QOclpn3dJ3X3cY2ptLRPAY8B/hMW9ksAVMnr5YB/pmZD7djW1CT7KsBn6IChXtn5pfa6+8BtgLWpeo/3UBNpl41+38DjRVdEwwLUgPu31L92VeB4zPzrxHxQiqN29OoFfFTgOdT9YbXaSl1p06GSb1aHYtfUitJlwKuAI7JzBPb68+mVibv2t5yPNW+PtaZALN9aXqiatWdTI2trqNqcP62s4q5q2TBB4B3UUHqrbxHqlfLEvJQZxwfEScB/wv8m0qb9aeuBTjTTE61++UKwGnAlzJz91H4FTQG9Cw0PZOaaL+Cmn9YBfgD8MHMvLKdsxS1u+fAzDx8dK5aY0nXQq6JVJrvl1LZai4ATgXObmP4TjAR6v75D2oMtmVmPuIYTNPT05etAxxIBRPXz8wLup41x+cTZViWA06k5izeZrBa09NS5x4FrA1cQi2Wf4yWrbmdM4FKdboB1Ydt5ByFZsTUpppGROwFfBLYGvhwRCw73LnZtK9/Se2+WIzaMv3p9nm2MU2jrRzdEvggtXX+bVRtlGOBz0bECzrndk8yZOYPgPOoIOLunSCibUxdNqBS/r0NICJ+RKWUXDIzL6VqClwGHBQROwFk5pepFFsrUxMQGzpBqulpE6GPRdU3/DU1iXAbtdLvo8AHIuK5bSHOmlQB8/uB24GvULtdJ7cHRAfo6hNlPip96b+pXYZvpyaoDoiIXQAy81bgi8Dn2luvBPYxiKjhdMZMXSnbvk0tAtyo/X0EsEZ3wKct0rmVWsy1vvdI9YqIFalUWCt3UgACzwT+Re0U2ysiJnbStnVNYHXG8H/JzLOpvmy7iFhmNv8KmsN1Ly5t338ceAV1b9wkM19Npf9bG5gUEePaRP1twN+othldfZ/Up7WZx6NSNP+WWlx/LnVvXJuar9i1BXdO5Yk0p/cAR2TVEn4kqmaiYzANqy3Y6vRrvwQ+AVwMnBMRr+/aETY5Kq38dtTCrwlUsHpKOA+m6cjM66l2dRbweiozxJTutkdt6riQGn9t4ByFRsIdiZoqIl4DHE1NjD5E1a04ATgkM/8ynfdNoIqZf4GqrfL5drwvLZLmbe2GdTq1Ynm7ruOLUCmQvkhNuu+bT9Tk7Ly+E7YxTUdEdHZ+LQrcQu3g2RC4umtXxVrUzsTVqbb0lXbcSXeNWEQsAJxPpTvaGbgZWIRKCfJuKgXzsZn512Heb3tTn952ERFfAC7OzG+379cE9qXSZ30mM49sx5cG9qbukx8DjsvMB2f39WvOFtOmA1yK6rP+ni3NX3sO+Da1M/9DmfnbtgL+w1Rq+XPSlIAaQnsWfEdmntS1i+IFwKNUn7UxNRm/S2be1xWo7uz86aQL3IHalbH29J49Ne/o6be6d/B8B3gY2Lm1qRdQiwXPBd6TmQ91fcYRwFcy8w+z/zfQnKynTXX6oQAOoRaabpGZf2yvPx34ERVc3Bn4QTv/HcDXgbOBT2XmFaPxu2hsmN4zYES8mlr4PAn4n8z8aVucsyewHrU4Z9t2jzVNs6Ya4hmyu29bnSqHsSmwfWZ+tfs9Pec6R6EZmn/Gp2geshyVdm3nzLwkIu6mdicSEdMLJi5Apd36hAEejcDi1OT71HaSmQ8Ah0fEo9T2+38A+3bd1BalAj/72MY0lNYe7gGWj4iHqd3RnwOubZNV82fmY61v+zQ1sbV/VC3FYxwwaUDLUfUPP5OZV7dj9wE7tQV+uwEZEcdmV02oDtubenVNvk8ANqGCPJOA73XOycxLI+JTVMB6n4iYkplHZ9Xt2Y+atD+Eqnd39Gz/JTTH6pmMPwZ4DTUZemtEHA78MDMvjIjNgDOB4yLiDCpzxLbASk5YaTgtaHNSW2RzUUR8EzgxM++JiA+20zYGjoyI92fmQ1GpmfeIiKMz88YWtF6tnXv/7P8tNKdp98OvR8RZmXlKC9qMBxYEXgmc0YKIK1I7eX5MzWM81O6Vd2fmkZn54dH7LTQn60yed3/d2tnKwD+6gogLZuZdEbEhcC2wdWae1c4/rQUfvwY8LSJ2yZZaV+rWNdZfCHgTNfd6FXBFZt6dmRdFxCepGojnRUQnmHgslZnr9619jnNMpo6udrUIlR1pJeDBiLgqMw/LzMsiYn9q9+HJbYr1/3qDiOAchUbGQKKmysyTI+LKzPx9+37fNiE63WBie0g8ODP/084zwKMhtYHPDcBmEbFUZt7Ws5rqOCoovU9E/CIzf9re96+I+GhWGjfbmPq0YOECwMuAB6hJqPcBf4mI0zPz0a5g4q/bpPthwG45TuzWAAAgAElEQVQRcSpwb/cgSpqBx6nUMgt2DnRN1H+aSh+yA/BoRHyxc3+UhpNPpMu9GFiWygyxBPCGiLgsW93XtkvsU8B+1KT8vzPzjHY/PZgKJv5kdH4Lzam6goinUQHqw4G7gXWoVG2nRsRubRJrI2pn4u7tnFd0JlOlXjFtzeD5gbuo/un+iDgjM/8TER9qp29EBYZOolbHT6QmvQCeS5UvWD8rHaX0UipguHxEPJSZ38zMycDkiLiIuj+uB3yTql/37sx8ICKWb++9Jlp9sVH7DTTHagHoLajFgbdRiwPvb0GeBYDxUSmZ788n0pXe2fqvnSLiv4E7MnNyZn6jve8wqg+UptEJ/rWx/jnUnBfUmP/4iDgpM3/bFnV9klo0+KOI2Dwr9ffv2ufMZ7BHHS0Q2GlXl1Hl626nxlPbRsQbqZ3Vl0fEgcAU4JSIWCQzj3P+S0+GqU0FDLkVempwp+3e+SRdaU4jYjHgOZl53ehcscaazmqXqNQzv6JWVG3UXutub8tTE1i/odKGRA6zTV8aqj1E1QuYQA2mnkGl+vtGCyaOg5pUjYiVgPsz82+z+7o15+uefBriHrk4cCnwV2pwfm/Xa0sAP6R2Xr+cqt1zjgsgNJToSisDHASsSq1EfhbwLiqV0U7AN3va4CRgM+BjPcdtZxpSRGxMTXJ+CPhxm3h4OnAHtZP1U5n5SDt3Uapm4i2ZeftoXbPmbF1j+8WA46l29GeqHvDGwEeoXWP/aYHGz1E17SYAVwPrZtXj6aQ6XThNy6wuEfF64PNUmzkgM09rx3ek7plPo/qzjdvxJdv5a1F1z02Rqz4RsTZwBvBP4L+ApamdYdtk5tURsQ8VyNm0s/Ow671HULv612j9V3dawMW6nwmkbhGxMPBLapHWBzPz2oi4CliBqmP32c6mjqg0p8cDd2bma5wD03Ci0t+eASxJ1UH8Uxvfv5NKF//LzNywnbsqtZhwAWCSbUpPhsVZ52ER8cKIWDMingMs3I7NB1NXxne+3pea1NoZ2D0iXkrVgLo6Ku2DNKSeNjaxHb6NqoW4bkScDFPb2/j29Q3AjcAqQN+KK2926mgT8J0Ht4UjYvGYNl3umtSq0M8Bb29tLIGDIuJjwHUGETWUiFiDStP2nrZirztQMy4z7wb2AF4HHBBVn7PjBcC9wNuoYPYeULtmZ9f1a+xoQcSFge2owM3XM/NXWXURd6NSGX0Z2KqzEKK97+LM/Gh7//xdx21n87iIWKjtjOjUpu5YntpFfVUbd70Y+BO1eGu/tuPiJRExITPvy8zLDSJqOG28la1f+hbwQiqV5P3A9lS9sMOALSJiiRak3gN4M5W++bVtEn5+amyGQUR1RGUZISs7zaeolN2fiIjN2/ETqbp0jwILR8R6EfFe4Bhqkc3bDSJqKC2I+DNqJ+vm1JzDtsBS1A59qIn2C6idO2+JiIntvSsDawNXdhYbtn6wc6+9b7b9IhpT2tzq3sB/qJrC10bEd6k5ss9Sz417RcRqAJl5ERUIWrd97xyYhjMRWJnKSHMDQGbeBXyV2hC0frTMEJl5ObAjVYs6e54TpBExtek8KqoeysZUGpn/AH+OiA+1jgWYmiqwMym/b0Q8TqWqWR14BXBQPlEbSprGMG3sw5n5uxZAfDawQ5uw2qpr5894apXWA1Qeb6lPTFvv6TPUyuNnAjdFxA6ZeWdW3ZQ1qJ1jh1JBnwnAVsBLHZCrVxtML0JNii5D1a/YIyI+C1ySmX/sCir+gron7gesFBHnURNd21MTCf8A/k3tipWm5yiq3dxMtafOTp8bI2I3apL9BKru5reypy5K7/ead7WgznnAohGxdlatsE7WhyWAxzPzHxHxIio7xPlUOsCHImI7asLqo1RqXWlIrX+a0nYZvpYK5uxK7dKnqz2dQgUTaX3X3cCVXZ9jnSf1afMPj7avD6cWQCxL1T8/tPVpp2fmbhFxGxWcPpu6h15HTZBeM0qXrzlYRLwSuIja6fXxbGnjI+JbVBrdXdqOnSuo9MsHAd8FfhURD1PpAh+lFtVP3ZXdeab02VLdotLhPgpT51b/Qu0w/HdEfIWaU900K+3k4sD7qdp2J2TmJdlqbUZPZhzN2yJioU7f1fwXlaL59tbO5qfG+/dFlfD5KBVoBKZu3DCLjZ40dyTOgyJiX2p1y2eAVwFfABaiBkjbdlYAwhPBxPb1Z4CfAqtRqbQ6tRNtR5rGdNrYRRGxfWbeSa28OgbYKCIujYi3RqWv+V8q7dHP05oWGkJ7aOsEEb9Fpf/7FXAS8Ebggqi6F2TmfcAaVAqtScCKwMtdBKGhtLmA+4Ej2qHfUGnaTgTOj4g9olLikpn3AEdS9VWeA+zV/twKvIFKGfIs4E8RMc4Vf5qOD1PBn+cBH2m7YDuTUjdTtep+CJxK1d+UhrMQcDqVpu2sqFSRnUDNj4Fl2sKIX/JETbH7I+KZVNuaQE2SSsNqq9jnp/qto6mx1e+6diiSmQ9RO61/QC3m2r7tvu7+HCdG1aczsdkmQN8KXNj+3plKG79fRLyznXswFUhchUoNvrVBRA2lzVlNat8+Qt3vOqUMHqGeFe8AHmrPA7+jxvgfoxY4PwR8B1it7eqf38CherUMSS8DyCqrsnhE7NlePgM4OirD22uoXfqd/up31MLBd1G79qfyXqmIeHpUvUMy8+H2/cltXHUDtUDifRGxfBv3d8Zid1EpnBfq/UyDiHqyrJE4D2mTmBOpyaifZuZ+Xa+tTK262pyqnfLl7oFRVO2LHamA0J6ZeWg77ioGTTXCNrYFsEtmHt9WXr2OSvPwQmqX9D+Bk9qDoTSsiDiISl+0XWb+ug3SPw3cT6WW3DAz/9jOHU+t1nqwrYiX+nRWFrcHvG9Rq9vfTqWbeTsVIPw7NQH/WeC2zLw3qg7B0wAy86ao+mJHUbuyJ2Xm9bP/t9GcaLhxU3sQPAt4GTXWOrx7tWlELEftWtzPHTzq1RYBLthWHy9CjecPoyam3pKZD7bUbIcD2wDXZuYr2ntfQKU+ejPw+s59U+rVuUd2fb87sC819t8wM8/pPS8iJlB923zAG5x410hExMuBc6ld+l/qCi7+D7UQdT5qTuLMdtwdO5qhNqf1fqpu2GHAIZn57/bapcD9mbneEO9bsAUbO9/b3tSnLbDZilr0cEJmnhoRN1H1N9+ZVXqFiNiECkqvk5m/bsfeR2WxuRC42LG+Otoc65uo58OfUvWnr6fmTTfJqkP9IWo8dg7w6cy8oS2eWJHasf8l51c1s5jadB7SJkeDSik5H0xdgTU5q6j07sBkaifG34Bzuya8lqZ2iu1rEFHDGaCNHRYRf8vMHwHfA74XEZOAx4AHOitJbWMaTkQ8l0plekgLIu4BHEDVuLgPOA04PSK2zMw/td2tt47eFWss6NoFdlVEXEItfHh+Zp4YEWdRqZoPowI6bwR+GRFHAH9oK/6IiDfwxOKI9QwiqqOtXn8sKh3gy6h75e+p+96dEbEptRBn13b+1GBiZt4I7NP9OaPyS2iO0wI1FwNHRsQpmflARHyHSg//RWpn4sZt5+EJ1G7pbSLiTCpl4ARgJWB9g4gaTmdM3hnXA2TmFyLiDuBLVG2nOzPzN53ngbar56GI2AiY3H18VH8ZjQWLUjXr/tjd7jLzvIjYB/gGsG9ETMzMUwzqaCTa4r+jqN06nwEmR8R+wJnUgtNNYJr+rtNfTd2p350ZR+rWxvh/osZZ+0fEoVQ673cD3TWA76XmJd4elZ55IjXX+tvMvBAc66t0LXK+lgoyb0stCPwtsCW1W5rMPCoink/taH1FG+//F/A/VHs7dPZfveZW7kicx7Qgz4XAY5m5bjs29SbVOp9jqRzxq2Xm37ve+9LMvKp9bYBHQxqgja1GtbG/Dfc5TjSotaf5syfNbUQsRO0SO5fK+f4N4JOZeVJ7/WxgA+BOqlbKn2brhWvM6po8eAFwGXBeZm7dXgvgT8CNwMNU6ualgL0z8+ColG4vBjYCvmO7U0dn9XrbrXo+FZR+FpUq6xvAyW1RxCLUytEVqaD1UVkpAqVhRaUrPajtSJzQgjeLUekADwMup3aMPRwRSwOvphZKJNXPndGC1dKw2s7XS4Gzs5W4aMd3Bj5HpZn/dGb+ph2f5nnR50eNVEQsS7WnbwD7tD5tfGZObrurr6YWQtwEvDkz7x3Fy9UY08Zau1LBxH9RC503aQsJ7ac0kLaDemHgkhb0WY9K6w21EeOQdt7UnaxRNRI3ofqxe4DbgTUNHqojItYCXgL8X1aa3BdRZVcWA76amdu386bWTIyID1AZu9alagb/AdimBbndSa2Zwtp284A28dkJ5iS1OnntiPgUTF0508mh/Feq1kUA67f3dV7rBBHDwZW6Pck2BpVGa0gGEdUe8vYHzoyIY9tuHaBywwOnZ9XbXJsKGP646+23Urtdr6QmSqUR6bq/3UG1qY0jYuWo9KXXUqlz35uZm1J92Htpq/wy8/Gs+puHGERUR2f1ets59nNq9eiOwLLAJ6jVpQdFxLOz0h5tRLW1g6kFE9KQusZWH29BxCOAAyLiaW1i/btUCqRVgR+2IOMtmXkasEVmvi0zDzaIqBF6OjWu2isiPtY5mJknUOUL1gY+FRGrt+PTPC/6/KhenT5sCH+lUjO/A3hT67smt2fO5agJ0o9S6QINImogbax1OFX/cCmqbvDf2mv2UxqxtrDhbGrhcmfO4XnAJdRY/n0R8W6o58SWlYTMfDfV/g6nymGs2ebMzBo4j+vMrVLzCyu0IGIAS1J1Nk8FNouIY2BqzcSF2tfHZKVnXh5YE3hHPlHT1SCiZgo7qblc63CWAO7qWt1yGZW+YaeWguaYdlNbIDMfzcwfRURncv5LvR2OAR51mxltbJQuXXOwtpPiEmARatJ9fWDziHheZh7RTuv0RctR9ekebe99BrXT52xqtdYjSANqk/JHU7URd6Da4ANUOpHOZMMVwBUw7c5rB+pqE+krZeZXu8ZNG1Erj/eh0hc9FhE3UimQzszMW9t98oGIeAtVh/O0UfkFNCYM0de8ElgBuDcijsjMu6PSnELtTDw7Ks3p1BRbZoDQSGXmvyLik9Tuic9GBJn5ufbacRGRVO2xoyJi+8y8bjSvV3O2nt05bwH+mwoe3pyZt0XE29v3RwJHR8TJwDLAB6jgz/daQEgaWBtrfRkYT5XH+FdEHJStVIE0Ellp4ydl5t9aMOf5LUPSSVGlew4F9m5jrS9n5iMRMZ7KDnhy92e1PtEdifO4zpg8M9cGiIiFqZIqZ2fmxRGxDG1OorWr97dg4jhgceDhzPxL5/PaObYrzTTuSJyLRcSHqS31N0TE2RHx1pYS5Bbg88CfgT0iYjeAzOxMwi9M7eb5+zAfLQG2Mc0aLfXflVSqmQ0y8yXAy6mdYDu3nWHdK0ZPoCYUvhQRBwDHUSknzzeIqCerLZK4mFoUsStVX2CLzOzU64nu8x2gqyMiXk2lZHtuVKH7jhdT9Sr+0IKI21D30E9k5rFtAcUGEfH0zLw/Mz/UFuEMt2NDAmohA0BmrkO1vQ8Bu0bE4pl5H/AdamfiysCFbXfP4+09BhHVp9Pv9PRhZJW9+AK1g+KzPTsTj6cWQNwDWB9Y09UVRDwd+D8qYHgpcHBErNqChGtTi7f2BW4DzgE2BnY0iKinKjPvodrdp6ix/l4RseToXpXGmhZEDGpMf35ETIpKkXsxsAc1p/HxiNihvWVJ4PudObLOM6ULUdXRM/Y6nsowskNELJJVGupgarHpO6PqvkItpP8htXBwKsf5mtmskTiXiohjqZXv51KTn2+j0pVun5k/a+e8klp9NQn4FrWCdEEq/dGXgXdn5jdn/9VrLLCNaVZoQeZL2rerd4LP7bXXAj8DVs3MK3vetzk1qTWFqjHwrmzpmKWnIiK2A04CPp+Ze43y5WgO14KIF1APfXtlV33DNuG+C/B8qj7dqTxRXzPaa2sAe2TmrbP72jV2xAzqnETED4C1qFTyh7ediYsC76RSab0uh6lRLXW0lG3fBr6Qmef3vLYMsDewE/DhzDyq67XIzAxrjWkIPTsRtwY+SQVxrqZSfe8J/AQ4MDN/14LarwNeSO3CuDAzbx6Na9fcKaqcxi7UXMUumXn0DN4i9YmqaXcG8A9gd+Ditvh0EnAIlW7y59RzwGLAKi5EVa/esVN7RvwltSD148CpbUf1Mu377ajFW/O1P6tm5uTZfuGaZxhInAu1XWIfoeo2XdBWvf83cDm1HfrdXeeuAGwNfLAdepSaiD8mMw+cvVeuscI2plklIt4GfA24CvhAm0BYAHgMeBnwDWoS9GHgxuyq69RSmo6n0jncPdsvXnOV7nR/EXEBVe9ilWzFzKVeEbEa9aB3AjUpOs0q0IhYmUqF+1NgXWDfzDyoPSCu0N53LfB+V49qOD2T8B8EVqL6p29RKXOvaa91BxMPy8x7WmBoXNuFIU0VEc/micnNmzLz+ohYGrgQGAdsm5k/73nPqtTCiSWA/TNz367XTJmr6YqIrah7X1Dtp9OvfYQKLv4cOCgzfztqF6kxZ3oLbaa3uKHdHzcDvmFwRzMyXFtqzwJnUzupd+OJYOIaVLD6xVQN2K2y6r7Ob3tTR6f/iqql+XzgX238HtRi+xWAvXgimPgcqgzLOsBdwHvziZqItivNEgYS5zLtge8EKqXk3pn5YKcTiYiTqA5mFeCxrsH6OCot4AZUKpp/ZeYv22uuJNU0bGOa1SJiZ2o18r+A3TLz0nb8AGr1e8ddVAqkr1FBxctm97Vq7BlqgmE6D4OdXRXbAydSu6hPml3XqrEjItYBzgMmANsDX2sTB/P1/L03tRjiGmBT4EGqrt3nqMn6tdr91El4TaOlOcquBQ5nUmm8b6cm4lehdu1/LjN/3M45C1id2v16gAFEDSUi1gS+AjybCgreTO1kPSIiXkiNs54LbD1EMPFnVJ3XKcBr7LfUqwVoXtw9To+InaiUkncDH8vMr0bEQp3FWl3BxAuojBAGEzVDXXMSiwAfBVak7pG/z8xTBv2cWXSZGuO62tkCwNLUQua/dHaBRdVJ/wH9wcSJ1L3yofZ8aTvTVF3taiKVyvQh4CDgdy3oPFwwcZq5DduVZjVrJM59xrc/383MB2Gauk1XUUXMF+2ZRJ2Smf/MzBMz80wDPJoB25hmiU4u+Mw8gSpM/t/AFyPieRGxOxVc3B14M7AJVSdlRWqX4nda2jZpWG1g/XhETIiILSNim4hYcbh+qGtC9FygU8NHmkYLIv6MCtbcQKXG2qq1tyktKNhpY1+jagivSe1M/CNwOLXLelJ7gBznZLw62qpkMnNKVxBxX2rh1lbAupn5cirzwwrAJ6NSy5OZm1Bt7K3U2E2aRkS8htr5dRG1CGITqib1gRHxzsz8M7ADFVw8NSJe3/XeNdq5H6EFEdtElwRMTcl2GrBnTFvz6TtUCsClgK3b/fLhNjFPZh4G7AdsDny40w9Kw2ljrcfa8+DvqBTyzwJeAxwbEV+NiIVG8llOwms4bf6q087OpepS/xq4NCI2iIgl2qKJjYFlqJrCa7X2eX9mPtjulfPZztTR1X9NBH4LJDXHdWUnQN2eAdaiNnR8lqqPuEhPEDFsV5rV3JE4F4qI52fmX7u+7+yo2I6anF8hM+/sen2a1fKz/4o11tjGNKt0t5GIeB+1mnR+4DlUTc7zu16fj9rB8xbg8uxKcyr16uqnFqVStT2XSuE2GfgAcFpmPjLE+1zlp2G1SfXzgKMz8yNRKZZ/Q9UD3hP4Zgte97ajlYE3UP3bH6g04Y/bvtQtIhYDrqR2E57Yji1I1a27LzPf0XP+DlR9zv0zc/+u40tn5i2z78o1FrRA4K+oCalDMvO+dnzVdvxsKmUWVArd49vfxwJ3ttfuBdbvWjTh5IKmEREvAG7PzPvbDte/tt0ViwOHUbvzT6NqbU6OiAWy1UiPiPcCP8vM60ftF9CYERHzU2m+l6BS/F3fjp9JpS1dNzN/0Y7ZX2kgXc+SC1GLbyZTCyIS2JIqw3IgcGxWberVgO+18zbJzD+M0qVrDtbVruangof/RdU9vKU9Gz6bKg+1cGb+rS3QuZhalLppZp41WteueZM7EucinRWg3QGeHvdTq5EndM6PiI2AvdoElwEeTZdtTLNaJ+Dcvj6OKkwOcCNwR2eiKipdLpk5ue1yNYioYXV2eLV2cxhwG7VSdENqQv5LwPsiYkLve3t2V7tKWVO1vupdwMnA3q2d3Umlm3yU2nn49nii3sW4zvsy8+rMPDwzD83M87qCjbYvAVODiFcAfwF+1PXSfFQKyold53buiSdRk1bbRMT4iBjfjhtE1DQiYkkqIBhUlpH7ImJcC+JcTi2I6NTUzKzam1tQCyd2pRZK3Ats1LVY0El59cnMm1oQ8ZPUwplXRcT4rHrmu1EB602Bw9timke7dmIfbxBRQ4mIhYc4vChVg+77wE3tvM2pndZ7ZuYvOrsS7a80iK5gzziqdt29wPsy87DMPBxYm0pH+QnqOYCslMxbUP3etaNy4ZojRcQaEbELTNMXLQK8CDgnM29uz4ZbAWdRu6xPiYjXt/MnUSnpfzTEx0uzlIHEuchwg6Gu449SnVNn0LUl1Sk90DtRKg3FNqbZoSeYeDy1Un48cERErNba2xQD0xqpNhCfQKUDWRQ4LjMvyaojtjsVSDwU2HmoYKI0lNYH7QR8IDMfau1sfGbeDqzB0MHEGK7v8j6pjpba6ArgemDbzPxn18uTqTSTr4iIl8HUPq7zXHc/8EhbaDN5dl63xo7MvAM4hWpjX4uIF2fm4y2IM55Kk3tz9+KGzPxXZr6Tqrs5idqJOLkFfxyTaUbOpibUv8oTwcT/ALsAP6F2jH2xtae+DBFSR0S8nOq31uo6Nh9Vr24F4JrWl21N7VDcNzMPbWP8QyPiTaNy4RqzWhBxASqg8w1qbuJamJqtJqnFhX8A9m+7y2jPm5t0LyjUvK0tZjgQWLLnpUWp3a3LRsTOEXEi1dYupUqs/H979x0tZ1W9cfy7UwghhI50kCb+QDpCkCZdehMQUDpIR4r0ltCRFkCULtICgggoCIj0XhQpIiK9SG8CCYE8vz/2ecObyb2XEJKZW57PWqzc+84747mus2bOnH323vMCG0T2E5akHZXlUPs0c/xmDiT2LJ8BI4BeEbEh2etpsKShrR2WdSOeYzbOqgzXtrQRTPwF2TPxpIgY5FOkNh4uIUuaLkZ+yQOgBH0OI0u2nQDs2M4pZ7OxSPq0Hqypbaq/RdvBRMWYfaLMxlCCiHcCUwJ71LMJSyD6M+BQsvrDkFIqsPrcnI7sCfVUREzS0ees9Vy19dUZwMnkhuiVpQQlZFbr+2Tm4ej1Wu15T0l6vpaJ6Exq+1Il03VrsizuRYwdTPwz8FPyAKFZR75L9v7dLyK+C6MPd71AHo5YLyK2I+fZIZKqOfU9MmPR63wbH1MDdwFzky0y5qrWZbUDNVcDc5L9EcfgA4MWEbOR+6VbSjosIvpHxOYwunrIMGBVMrN1HmB1SbtK2p/seT6NpOH11/QazJrNGxk9QG0TYQR5Snkr8mTDsZIGl3s8F2y8eY7ZV1WVByk/z9LWPRq7zOnxZO+BIyKinzdI7Svaly++/G1UzzyU9A5fBBNPIftxmo2X2oZCPZh4HLCJy3xbR0o5038AC5KZh1tHxIDyWK8SiA5Jj5O9XVcgA0CDI2JP4Bxyo/SIEuT2oRsbS8P66jzysENf4JqIuAP4NrCppBH1kqVtvXf5/cwafclBwSeAbYA3GTuYuC9ZKvycpgzUuixJ5wA7AcsDh9WCiR+QB3F+Sq7ph0g6ppRtnhcYAnxEVkwy61CtJUFVPv51soLNaWT26w7kAfqoBXMEfEIesDcbLSLmAJ4A1pT0WskkPBU4NyL2ApB0PLARsCy5Dru5tCqYD5iGDCaatVT4+2XPERGDyKasAIdKOrpc7+UvgTYheI7ZVxURFwPPSTq0g3tGz5+I2Ba4Q9IzzRqjdT31QHXD9dnJk6LTk5vwf65nk5Vsni2B03y6z76uEkz8LCKmBe4lTyivWUrqmo2hBBEfBp4hN0GHkj13zgWOUfYYq38e9gGWAk4nT8Z/QvYT3kPSY238T5iNoWE+bUf2q/sWuXn1+/Y+S80alQMPawHXl/eqDudORHyHDBpOD/wYuL9k9Ps7o3Wo4X1rJ7JE4D3A0ZLuK9dvBFYmg9KXkBmMmwKTAkuUtZnnmrWrtoYfQB62eU7SieWxWYA9ycMPpwDnkT05FyDbZfwXWMufn1ZX5s09ZDBwQ0kfRcRi5GHTuYEzJZ3U8JwBwKLkgfpJgKW9R2Gt5kBiDxIRC5CNp0+R9MtyzQsom2A8x+yrKCeW7waekrRttWBv517PIxsn8UUvul7kgrsX2S/s8/L4HGSfnsnJL4E3qI0+Yh3NR7NxVduI+AbwS+BHLm1kjcpp93eBR4CfSHqpXLuKzDCsBxN71+dQZK+VWcjM1/ckfdj8v8C6qoZN+R3IvsGfARtL+qfXXzYuIuJ8smzpLsBFZYN0XIKJ55Cb76tLurcpg7Uur4Ng4rGS7inXzwUWBxYiD+k8AexQqxrhNb61qfZdciC5V/E28FfgF1VZyYiYlSzJvDfwGllWdyTQB1jJByOsUdn7Gkp+Vq4p6a5yfUEyM3FO8jDzqeX6lMDFwAxk1bfVy7zq7e+S1koOJPYwETGnpOfKz/5gswnOc8za0/Clr1qgXw1MJ2m5Fg/PuoHavJqcLDvzbfIL3e3kJvy75b4qmDiA/BJ4k6RPWzRs6yLG94tb44aVvwBaWyJiYeAtSa9Un5cR0Rf4HWMHE6vHvc6ycdI4VxpKzDdmJu5PtivYpAQTnZloHSobpLeSmRMHAheOYzBxEbJP546uNmId6ejzLiJ2Bo5i7GDiQPKgzQvAcElyENHGRWQLjKhonIkAACAASURBVFvJfsG7A8+WIHTf6gBqRMxYHvsZOfd2JjMXP6/fZ1Z9FkbE9MDjZPb+NrXH68HEoZKGluu7kD1dTynzyu9f1nLuWdaFlAX6133uC+V3bzzYWDzHbGJpLMdW20T/BzBlRExaMsjcT9PGS5ljVRDxXmB+4ErgAbKPyhWldCmSXiBLcH0AXEGWPDJrV/kC+HlETBYRv4rstTNOGr/wOYhobZH0qKRXys+jSsB5JLAxuUG1PXBQREzuIKJ9FWUujYqIKSNiPYB6cKeaT+Xn88gSWr2BOyLimw4iWkfKul7AiuQG6QnAVuW9Sh19v5T0d+AHDiJaR8ocGxURk0TEdyNipYhYqHpc0q+AQ8hDNwdGtluhZOg/LemTai56E97G0YrAtGS7nqdLEHEF4NDyPWBJSf8FziIPr64M/LiqiuMgosEX+1rl/acX8B5wObBhmU/VHsZjZED6OWCP+KJn4pmSTizzqrffv6wz8GZtF9FwanShiFgrIhaP7Kcy+p72nl9bOFUbDn0m8pCti/Ecs4mpFkT8LfB0RAyLiAPIU6ILkGVn+tbvNRsXkX3Cqo3QfsAw4A1gHUknA98gS/4tAlwZEdOU+18ENiSDjfe1YuzWNVSbpOUL4MJk/7pDI2KuFg/NurHapkGHwcTWjtK6gjKXBgAPAutGxMxt3NMYTPw1cAvwUlMHa11O2WDvrbQM8ChZ7m/riBgwDsFEV4SwdlWb5yW78M/Ab4HLgFsjYvvqvlowcRAZTFymXB9Vu8eHImxczVz+eyki/i8iBgN/AdYDNgOGRcQM5fvkGcCJ5Lw7yXsZFhFTwxh7YCFpVFnTDyOzDFf84vYxgonPAkdHxKb11/RBVOssXNq0i4mIrciU577km8/lZB3le8vjbZYPaQgS7Q70I1OmfVLGxuA5ZhNLCfIMIQ+xfJssfyQymPgB8G+yB8GTwKvAA5LuaM1orbOLLIf1D41Zqm05YD/gcEmPRMSVwFLA+uW/g4Gbgc0lvd3wei43aWOJMfuknE5m6awFTAVcC/xM0vMtHKJ1c7U5WJU5/S55AOJgSf9r7eisM6t/rkXEqsABwA5k6bU2NwEaKkhUpbj8+WijRZb8Gyjpjdq10eXWIuJxYF7gY3LdNU5lTs0a1d6DBpCHad4D9iUPCP6JDPQcIOmE2nN+CvwKOFHSfi0YtnUxbb03RZag/Bu5H/Y6MDXZQ/iPwKzAY2Tf8yvK/TORgezNgPkkvdm8v8A6k4hYjFyv/xU4BnijfAbW12RnAT8Elpb0dHXYprzfLUb2UdzLay/rjHyKtZOrn96LiP8jS4WcAKwK7AasCQyp0qLbOvHXEODZjWzw+q4DPAaeYzbxNM4TSSMk7S/p55LWAeYmF9tPk18G/0oGsFcFfk4GE83GEtmT4mZyM6HuIeA64NGI+DmwGLCxpIeBw4GngGWAuyJiqvoTvVC3tpQAzmTA/eTGwfXARsAvgJWAMyPimy0boHV7bWQm/otcm/Vv7cissytzp39EXAXsCvxb0rMdBXNKZmJ9Qyv8+WiViOgNXA08EBGzlGt9SsZYv4h4AngHmIcsc3ocWeb0SzMTzRpVBxnIvYm3yL6tD5IB6lHkZv1xEbF37Tlnkeu0A1swZOtialVHekfE5BExfURMVgKBy5P9qY8FVpZ0iaT3yQD2v6ll7Et6DTgS+LaDiD1eP+AVMlB4P3B+RCwO1D//bgImBaqsw6ituR6RtEe1/m/qyM3GgTMSu4iIWAKYHVgH2FPSB+X65sAp5EJ9iKTby/X6G1E9S+xUYAdJ57fi77DOy3PMJqSGE1dTkwHC4bV51VfSyMh+di8BB5WSNNXzByr7WpiNpQR2FpV0d0RMCoxo4yTp1cAnwPaSPo4vyrq9QJ5o/rE3R21clNPtg4E1JP2tXJucDOacS5b/20fSs60bpXV3tczEPsCMkl5u9Zis84uIdcnsnIHAmZIOqNZgLR6adUElM3ojcmP9LfKw1vOl6sjDwIfAZlWmfkTcSZYE3w+42FnU9lVFxLRkub+/Sfp9ZJuMFYEfACPJYOKC5P7F6Q3PHZ0pa9aotq6aHDifrJj0TeAu4AJJvyv39SqHbCYhD0n8mvyOuUZ1+MbZ1gZjZVHPChwErALMAFwBXCfpsnLvVWSFrnnLPPQ8si7BGYldQEQsCtxANvHtJemDsohH0qXkwuo7ZM+UFcv19gI8P3WAxxp5jtmE1BBEPJ0sAfIUcF1EbAdQgoh9yobC02SfxNENqQFvNNhYImLGiJhO0scliNiH7JfybDV3IqJvCS7OA0wt6ePy9NnIIOKBZGlTn/KzNsXYfeeqwxBvl8ejvHddD5xD9ksZEhGztvN8s6+tlpn4mYOINq4kXUuWW/svsEdELFzWYH6fsq+sBKB/D+wFzAhcFtkv+EEyiFgFFqv5tTwZYDwT2NQZifZVKVsRXA38MSLWICuLbCvpCUlPA1eRQZ2hkS1a6s91ENHGUsu6r/oHP0weqL+efK+ai+yBuEu5b1QJaB9GrvsnA9Yu13s5+GOVai5I+kjSvyRtBawBHEF+Hl4UETdGxGZkr9f+wP7155p1dv4C0TU8Ri7YJwMGRcS05QtgFei5DNiD7AN1fETM0hDg2ZUvAjzntuZPsE7Oc8wmmFoQ8XJgAzJIfSpZqvSciBhc5k/15e4xYMmI6KfSl8cLKWtUNqqeJjdCpy6X+wB/AAYA95YvcyMlDScb368eERdGxKHAxWRA6B+1gxDOSLQx1E4d96tdfgWYgjxZCtC7Fky8EXifLF9zEuSGQzPHbD2H37OsI+0djpF0AXA0GUy8vAQTRzmYaOND0qfk2n538nPxGbJn3XrVIYcyv3qX9fxK5KGvu7y+t4508B72SJl385FlA58v9wcZ0L4U2Ba4pDkjta6oBA2rA/HV598RwOdkJvUBkg4AfkIGr0+LiI3KfYsC8wNPAoNqh6K95rc2VXNM0j8kHUVmUe9KHnY+s/w3EFglIqZr2UDNviJ/eehkGk/p1TbbdwUuAGYi+/FM0xDouRzYEzhH0iu1AM8uwOlkqUkHeMxzzJoiIjYBBgFbACdIGgKcXR6embIRX37/hNyk79P0gVqXUcpG3kv2RdypZCYOJ+fVwcC8wH21L4Y3kSdH1yIblr8JLOfTo9aRWumiGyPiqHL5JrL/5qURMUfJCKvmz4zkCeadgY0jYsPmj9rMerqyofl5REwWETtHxEkRsWtErAIg6UIymCgymLiQg4k2viSNIIOJe5LtL/rRsI4v87GP0pqS/tWCoVoXEV+UmRwQEftGxFERsUrDwa7ewPTALBExDVmGcgHgUUm/Ufbq9PdJG0tkj7qrImIF+OKwA/B/wAuSnqsC2co+nCcAzwJblpe4G9gF2LHMs97OeLWOVEHmWgbs48oerguRJU9vJxM5JqNUvTHrCtwjsRNpyPCajmy+OoLsK/ZhCeicTPYluA3YVdK70Uafi+q1IvtiTCPpN838W6xz8hyzCa0sjCYpGwr16wcCWwHLSHo7IuYBHiA33HdU9qxbRNLfI2IR4BNvMFh7Ysxyub8jM10PBc6X9Hpkz8QtgOOB/wBLlS+IfYGpyAX6i+U9y/1SrEMRMRXZH+UFSWuVaz8CjiJLnG4BvAZMS2ZbP0hmwD4CHCjpjFaM28x6plom9UDgfmASMsNiWnKdf56kw8q9W5P96kYBW0l6uDWjtu4gspT8D8hDpa8DG0h6qbWjsq4qslfdfcB05HpranKddXoJ9PQB/gIsTlYpmYasCrGE1/bWkYhYlawicgtwhKS7y/UbgZkkLVR+H/09MSJOArYhe9i9XXst97Kz8VLf0yi/rwncVILTvZzhal2BTyB2Eg0Bns3ID7l/kmUbfhMRq5VAzt5kHfjvk6n2U5essTGyzKrXknStAzwGnmM24UVEf7JHys8jYraGh6cDpixBxFnJIOLNwE4liLgpcGBEfEPS3x1EtC9Rf//ZGngO2AnYNiKmV/ZBvITsMTA3JTNRWeb0TUkvVGVsvNFgHSmfle+RG+1rlM9LJA0j+2u+TB60eYQ8GNEP2IdcU78LvFe9TtMHb2Y9Uu3gzFXkIYf1Jc1HlmF7GTgkIpYs9/6GzLSYmXzvMhtvpTJEVeZ0BuDqiJiltaOyrqa2ZtqOPBC4HLAkue76GXBwRMxT1vAbAueTgcQ/UIKI4b7n1o6ytr+ZPPSwInBkRCxTHr4NmLdk8vduYy79B/i4/noOIlqlrWpvHd1fOxhdZSleX2VSO4hoXYUzEjuZsmF1IVkv+QmyXMPm5Ims3SVdXb4onkCm2d9NNjUf0fYrmo3Jc8wmhHLq/Xoy2+tuYF9lv7Dq8R8Bp5FlJ3chA9c7SXq/bDCcSPZT2bX+PLNGDZkWtwEvkGVMpyP7ChxNllx+q5aZeAzwP2Auf9mzjjSeDC3Xgtxk/x3ZU2yH6iRyyeZfGZiFzL64rMzPYWQf4eVUekSZmTVLZB/hG8l+T1dKGhERGwCXk5nSJ0VEf0mflPvXBG5sfP8zGx+l/OQawClkNuzykl5t7aiss2sjO+dYco/ygNq13YGhZPDwGGWrg8bXcbUR61CtmtZawDVkWcn9yZ6Hd5OtCo6UdGa5/1vk5+djkrZs52WtB6ved2p7FdW/zli1bs2BxE4kIqYnT/Q9AOxT+6K3NtnnaQCwpaSHS1mHXwH3STqvVWO2rsVzzCaEyEbl95E95w4HHpQ0vKH85BRk6ZklgHuA1SV9VLITBwOrAys7E9HGRWTPulvJUmx7Ai+R5YxOJOfS4cC5kt4swcQdy/W1vUlqX6bMmdmAl0p2a3V9b+BYslTu39t57jJkJv/3gZUkPTrxR2xmPV1j24HIXog3AQtKeiIitgAuAg6WdGxZu+0PXKfs/1Q9b6zDFGbjo6zV1ie/U64j6bkWD8k6saj1RCSzoycFZgeulXRFQ4nJ3ckSp+cBJ0t6qmUDty6pHBLsK+nTWnD6ZmA34A3ye+a3yao3rwJzkJmIVcarg0M2Wu39a3KyvcWM5CH5AyQ92drRmU1cLm3aIhGxVmSD6LopgG+Rm/KflEAOkv5IZvbMQ27KUxZVO1YBHpfQskaeYzYxlFIfvwTeAbaXdGcpa1Qv1dBP0gfAWsDjwFzARRFxDrmptRYZ4HEQ0cbVQuT70zmSHinlSv8laR1y4/RgYLuImKEEgn4NrFkW+C51ZO2KiF7ABWSp7/MiYo3aw6cC/wKOLqWcx/gsLNnVK5CbXys4iGhmE1NETBERcwCUtgMDI2KT8vALwNvAMhGxJbUgYnl8ZTJrun/9NR1EtAlF0qdkqclBDiLal6kFER8m2xVsT1ZJOiYi5qwyfcq9p5MHCbcng9Vm7YqIJSLioIbLvUoQcQmy5/nN5OfiBcD0wLLAoWQg8QPgCr4IIvZxENHqyvvXZGSCxkJAH2AB4K6IWL/aZzXrjhxIbIGI2Ins5TRFw0OfAiPINyKqD63y88XAs8Bq5TXq/e58OsbG4DlmE9Hk5CLpBknP1oM0EbFiWbSfGBHrSnoTWJ48PdqXLKN7N7Bse9k9Zu34jJx79flWLdD3I8uY7gjsGRFTSRpeyteEN0mtUrIlGonMKDwImBO4LiKujIhtSq+K3wPzAd+pXmb0E6VXyPLNm0t6fKIO3sx6tNJ2YCvgpIhYqmywPw6sWt7bniFbFpxCrrsOL5mIvSNiXuDn5OboXa35C6wnkPSpWxZYRxo22HcgAzerArOSrQkGAGdExDercoEAks4ANiGrkZi1qcyXjYCjIuKQcq3KHluMLGl6uaTVycPNg8hg4rySTpK0NvBDSYeUvbLeLptrlWrvqxws3ZB8/1oPWJOcT3eTbaQcTLRuy4HEFpD0a3Ij/fmI+HZETFseeoc8Eb9+RHy/1Fj+LCJ6RcQ3gJHl8TEa/DrAY408x2wimprcbK8C0J9HxNQR8Tuy38BRwK7AHyLiMEnvkZtZ60hatSzKn2nZ6K2repvcAF01IiaF0VnTAO+VxwcAywHvV0/ye5dVImJR4JcRsU7jQ5JekXQcuUG1BRk4PCUibgHeIrOqtwIowcXRJL0l6X3MzCaiUsb0ObJs98nAi8C/gUOAUeXzblNyHf858F5EzEe+p11E9hTerL4xb2bWbGXvYUBEHEf2m75F0hMlCH0IWVVkYeDMiJijvGf1Ls+9sn4Q2qxRWacfB/wCGBIRg2tBxDuBi4G9ymHTG4G1yWDiyRGxUnmN+j6YD6TaaLVM6tOBFYFnJL1UMvL/Re6D3U4e6FrP71XWHflLRJOV06RIejwiBpHNfXePiOklfURmVEwJHA9sUJ42JXlKa3bgkeaP2roSzzGbyN4jN7I2i4j9I3uIPQisQ/bfnB9YiVykHxERy9Y33l0i1zrSXhlSSS8BQ8hN0r2qMpPFbMBTZIB7hSoTcaIP1rqMUub7YmA74JqIuCIiti6HaeqBwZckXU6WOtoMmITM4gFYzPPKzFqptCLYmWxDMBlZ7vv1srHeV9Lr5HrsfjLT+p/AXsDLjFmibVQ7/xNmZs2wMllRZJ/qQq1K0mDgHLISxBkRMU9jMMcZYtaRcsDvaPLQzaERcTZwGyWIKOmj8n2xt6Q/k5lkK/LF3phZR+YGdgG2AfpVF5VeJPtu3kZWrdnMh7esuwkf1m+etspDRsS1ZADnSOA8Sa9HxNLA1WRZyv+SWWTzAcdLOqrJw7YuxHPMmiEiFgSuI0+R9gbuAM4C/qTsjUhErEz2HvippHNaNVbrOsrm5meRTcuPJLPA+gB/BoZJejMihpIn/a4C/kpmXewEDAeWrzItvElqdeUL3MXAj4BrgSWBGYG/k30Q71Q7/ZwiYlMySH1imZ8u9W1mTVd9tkXEUWQ5rRnIUqaDJd1S7umr7J0Y5PvWrMDTwOtl07SPN+DNrNUiYkqyHODRwKvAOpLeqEpQlnsOBQ4Dhkrat3Wjta4qIgaSfQ93I8t/LylpeMM9UT4flwIe9mekNaq/L9WuLQFcSR463ULSrQ2PzwYMAz6StFrTBmvWBA4kNkH5UJpB0rXl992AhSXtUH4fBvwQOBw4u2yWzgxsSfYie4H8ULu63O9NUhuD55g1W0TMSgZ6+peyINX1qgfBusCZwFbVBpdZe2pf4iYns6I/JsuDzAbMDLxBZlm8D2wODAamAj4kMy5+UDZP/d5lY6htvs8D3EMGFA8AfkZmuC4KPA+cBNwh6bH68xpey5vwZtZU7R1eiIgNyUNcT5HBxL+U632A3pJGNNzvz0cza7q2NuHL9anJYOKp5PpsM0nvNwQTtwF+6/KSNr4iYipg//Lf4JLx2njP6M9Zr/WtrrZHMRlwhKT9ao8tRR6ufxbYR9LdDc+dAXjTay/rbhxInMhKmckfk+UZ9gA+Iesl70+ervq03DcM2Jg8dXVuyRprK7vMXwJtDJ5j1hnUF92ljOCZZKBxbUlvtHRw1iWUsqYXkyWWt5D0fLl+BXkQYmNJV5Vrs5IZ1X2Bx0qgyF/8rF1lI+EcYDXge5KeiIh+ZGB6R2ApMnh9I1kK6V1JH7ZqvGZmtcNZVVms6eprqoj4IfArMph4mKRbI2Im4Fjguuoz08ysFWrVRvqTa/lZyTYZV5aDzZOR/amHAnfzRTBxjDV9e8FIs3EREVOQe2B7004w0axR7f0ryKzWocCFkrap3TOIrHbTZjCx3OP9VetWHEhsgoiYnSzFtg8gYE/grPLFsL75XmWNHUoGet5s1Zita/Ecs86ilD3dk5xny1XZPWZ1ETFJdcihdm0K4FZyc+HYcm0DsozpvpJOjmxu3qsxwOMFuo2LiFiNLJV7cG2OTU6WB3wT+B+ZoTiQMudaNVYz69lqQcTJgROBBcn3pj8Ax0r6pNy3EXl461WypPyywLTAAj5cY2atUqsIMZDMOOwNTEfuVYjsMXY10J8MJp4C3AVsKend1ozauqtaMHEvMrPsyBYPyTqxhjXYz8gDp4uTrTEukrRV7d5BwDVk+dxDGsucmnU3bvrZBMqGq4+T/3/3BqaoTlSVEw59y88/Ai4na8XvWU7Km30pzzFrtYj4RkRcCpwGLAOs4CCitaUstk+LiPkaHhoIzAt8VO77ERlEPLgEEfsDPyd7vo7BQUQbF5JuIk+N7h0R05bA9APAW2Tp3I2A75EZiae1bKBm1qOVDfhqA+sBYH7gJuAK4BDglIiYBaBkHW5P9gzegCwB/p2y/u/dkj/AzHq8EkTsR667XicrQMxLbsh/TGb3zCXpY7LX2M+AtYCDWzNi684kfQAMIVsZDI6IbVs8JOvEyhpsAPAgsBxwO7AtcBuwQURcVrv3PmBdYGlgs+aP1qy5+rR6AN1dLUvidWAHYDHgmIgYJekEgNLXqY+kzyRtUcpvvd7Y28KsLZ5j1kkMBP4P+AtwpqTnWjwe64RKybV7yq/9I2KwpGfL78PJjIpFIuKnZLm2g4ATyuNLAKuQJdzMxtf1wNpkKfDNyD6bW0h6rTz+NrAvuE+KmTVPREwqaXgti6cfMIz8XNxc0hsRcRXwAbmZNWVE7CvpFUnXRcRDQACvlX4+fv8ys6Yp+wsfSRpZuzw/8E2yWs0TZU9iLbLE6WGS/lNarfwvIq4h12c3NXvs1jNI+iAijgZeBH7b6vFYp7crMBXZHuqfJbj4MHnYYbuI+I2krQEk3V8qc3mfwro9lzadCNrqO1d77Jtk+cldgQMlHV97bClJ9zdlkNaleY5ZZ1RObX3mALW1pzQdv5TcQJgd+CuwWxV4johdgdPL7UMkHVGufws4nwz6rO0+KfZV1T83I+Ju8tToHcA2wPPtfaaamU1sEbEQ8EtgFUkjSk/E7wL7AadIuisifgcMIjOnlyKzec4GjpL0csPrudy3mTVNRKxIlibdWNK/a9c3Bi4DZpP0WkRsAVwEHCTpuIiYksyyPrJkjFXP80EIm+g8zwwgIhYD5pF0RcP1M4EfSJqr/N63HIaYnqyatCy1Mqe1g2Du6WrdmkubTmANG1XfiYiVI2LDiJgXQNLz5CLrl8CxEbFvRMwWEZsA90bE2vXXasGfYJ2c55h1VpI+chDROiLpdeAhsgTzT8kswzMiYu5yy1lA1bNijojYNiIOIIOPA4B1y2lAl2uzr6Rk6FSfeReTQek7JT3nIKKZtdgCZFn4ITC6XPdr5Ab83RGxD/l5uamkB8hePK8BOwJnRcQ09RdzENHMmiUilgNuAO4nM73qngZGAUtGxDpkEPEQSceVx5cjD3YtWH+SgzvWDJ5nPVukycm11txt3PIkMFNELAqjq7z1lfQmWSL3dWCliDitPD6q/OsgonVrzkicSMppq2PIhdMMwD+A8yWdXR6fk6wDvzvZlHVm4BeSBrdmxNbVeI6ZWVcSXzQt7w/8E/gdcCdZWuYuMjPx+dLT9afAzuR72xPl/t1KzyefHrWvpfQWux94UtJqHWX5m5lNbOV0+wXkZvq2km4p16vPzevI3odbVhtVEXEL8Ar5ObmGg4dm1mwliHgLcAbZ0/yThsfnAC4E5iSrkewr6ZTy2HzAucDLZIl5v4eZWdNFxBySXoiISYHlJd1Urq9Kvn/9maz+8Gy53hvYH1iSXJstB6wm6ZmW/AFmTeaMxIkgIjYFfk1mVswHbEmeIj0wIvYAKGXchpD9ef4IbFMFeEo5G7N2eY6ZWVcQEQOrn8tm6CTASOAS4DvA38ig4QpkZuI3JY2UdAZZLmQBcmG+Uwki9nYQ0b4uSa+QB3FWiYiVHEQ0s1Yop+F7ldPtBwPTAVvWK4ZExBTALGRWfp9ybXGgH/BLSauXUlpe25tZ00TE0sBfyDLLh0j6pHofKge2kPQCmbkzKfAS8EZETBURPyQ36AcAP/F7mJm1SgkiBnAF8JtSyQ1JN5Ml5LcGDislUAEWAtYEbgaOJfvALohZD+GMxAmkVg/528B5wHWl7vvCZA+eW8kvgbMDR0j6VeNzG382q/McM7OuJCK+Rx5iOB94oN53ICIGke9ZO0i6uByOOAe4HdizOvHX8HrOGrMJJrKf8C+AzRycNrNmiuyJ2L+xb3kpYfoLYHNJw2rXDwKOIg8QvkZuYI0AVizfDfz5aGZNExFTAX8iy5J+S9IztQzqxcpje1Zr/4hYF9gbWAwIMqj4b+CHpVyge4qZWUtFxLJklvQnZCW3S8v1w8lS8tOT5UwnA54Hvkf2rL4K2EDSXS0YtlnTOZD4NUTEEcDwWo13Sp+6E8iFkoC7gT9L2q6c2rqd/AJ4mqSTmj9q60o8x8ysKyobDNeQpT6eAAYC/yJ7t94p6d2IOAFYCVgfeBX4IXnq7zay9JHLg1hTuFyumTVLRMxObkBBlsa6VdJD5bEFyM/BackN9sdrzzueLPn9Hvm5um7ZgPcBQTNrqlICcD0yG+cdYKOS1bMY2bbgEmBPch9D5TmzANMAc5BtV54uByG8BjOzpmpItIja+9Qg4GLgf2Qw8ZJyfUWyEtz8wFPAWeXgxGXAIsD3Jb3egj/FrOkcSBxPETEz2ZR1YbKUwxm1x2aV9HJEDCVPXW0OvFIWSrcBc5HlHVaT9Pfmj966As8xM+uqygbD+sA+wEzkZsJO5Em+PsB+ZL+UrYH9JN0aEf2AdciyIidK2q8FQzczM5toSvm+G4BlyKycfwJ/k3RkeXwrsvLIMcDRwMjaZtdcwHDgv96AN7NWKu0K1gROB14ks6avAC4F9pL0cbmv3YxpH4Qws2ar1k7lPWwmYEbgUUCSRpSqSr8lg4knVJmJDa+xPLA9sC6wgqRHm/cXmLWWA4lfQzlxdQjZ2+kISaeX673J/pN/Jb/obVyuz0Cezvoj8Jyka1oycOsyPMfMrKsqwcQ1gNOAp4FtydLL2wCrAY8AawNXStqkPKcPsDxwhzdHzcysO6m1KdgM2IA81T6K7HX+IrCbpMcj4jTyoM1Skv4ZEZNI+rSt12ryn2BmNlo5BLgGcAqZaXgpckvZWwAADVJJREFUsLXX8GbWGdVKMA8kqyfNRe5PPE0mcZwp6c1aZuKHwHGSLq+9xnRklaXZgR0lPdbsv8OsldzQeDyURqxIeoQ8eXUncERE7F6ufy5pJPAksHJEzFnKvK1CLrCurQI8biptbfEcM7OuTtJw4Hpgd7IMyGXkAYdtge2Ae8hN1P9FRP/ynM8k/bWcEuzToqGbmZlNMLV1fRX4+zPQH5gbGEpuxPcHhpUSpteTmYrnVkHE6jUqDiKaWatJGkFmWO9DrunnJ7N7zMw6nRJEnIzchxCZtDEIuI+smHRKREwm6T6y6ttk5drKtdd4i9zfWM9BROuJHGD4ihpLM7QX6CmuIfs+/Qe4lyxTc4GkZ2vP95dAG4PnmJl1F7UNhp3JU3vXRcQskm4svV+/B/xM0idtbJL6NLOZmXVpEbE4cGJELFJdk/QusBeZlbizpH9JWgoYBiwE/Ab4DJgH2LOj0oBmZq1U1vrXAweRLQz+EBGztXZUZmbt2qr8uw8wTNIDwE3kga67JH1cqj48AOxA7sPeVj25rMnekPRGk8dt1im4tOl4iojvA59Iur/8vgR5mmE5YIikoeX6cmRZyqmA+yRdWa77C6F1yHPMzLqLWumj04E3yBN8L9ced4k2MzPrVkorgsOAQ8kqIsMkHVV7fBdgX2BXSTeUawsAPwb2L7edLWmnpg7czOwrauiZ+F9gfUmvtHZUZtbTNe6LRsTZwCBJC5XffwxcCBwi6dhS9nRJMqg4ova83pI+b/LwzTodBxLHQ0RMD7wM/I3sZfFQuV4P9Bwp6dTac0a/eXnD1L6M55iZdTfeYDAzs56mZNsvDpwJLEyWzzqQXONPAZwLvAQcKunt2vPWJQ/g7O4MfTPrCsrBwR+QJZsDWELSm60dlZn1VBHRp7RMmQqYRdITEXE6sKykRUvP6kuAgyQdVw6A7QfMAAwuFSTMrMalTcdDWQytSfa1+EVEfLdcf4gvSlAeGBF7155TL1XpAI91yHPMzLobSZ+SZU53I0sf3VMOTZiZmXVLSg8B65KbUzOTZQCPLbcMBbYAFgOIiL7leddK2tk9g82sq6i1NDgAeAR4p7UjMrOerKyhBgB3ALuUw133AAtHxDnAb8lMxOPKU75F7sOOdBDRrG3OSPwSbZWHrK6V0pN/IE+U7ifpwfL44sAQ8hTpopIebfKwrQvxHDOznqRkJm4IbAr80CVCzMysJygBwemBE4H1gA+AzYA9yGzFpSS97coiZtaVRURfSSPLzy4HaGZNVWUilp8PBlYHtgOeIROqziV7JV4FbCnpk4gYBJxCZlMvW4KQbhdl1sCBxHEUEYsA70l6vvxeBXpWAK4BHgYOLA1ZiYilgOkl/bFVY7auxXPMzHoKbzCYmVlPFhFbkJtaKwB/J0/BXwD8vN6Tx8zMzMy+moiYHNgL6A+80dAWakFgbzKYeAswDdAb+Aj4vqSR3qMwa5sDiV+ipD5/B3gUOBs4RtKL1WMl0LMRcClwHXCypHsaXsOnSq1dnmNmZmZmZt1ffc0eETMCGwHHAAOBK4DNfPrdzMzMbPxFxE5kf2qAXST9uuEwcx9gY7K0fC8yceNySZ/XMxrNbEwOJI6jiDiJPM1wOhnIeaH22FTkKYZFyTeftSS90ZKBWpflOWZmZmZm1r01lsoqVUbWAoa4lJaZmZnZ1xMRMwPbk3usD0parVwfHUxs53nORDTrgBu3N2jji10o7RMRnwE/L5dPrkpQkqnS/wZ+RQZnHeCxdnmOmZmZmZn1TG18D7gfuL/87lPwZmZmZuOoreCfpFcj4jwy2/DQiLhI0k++rGypg4hmHXMgsaYe4ImIeYFJy8//ljRc0v6lDOW+QN+IOBV4nmzcOi+wr6SXG1/LrOI5ZmZmZmZmMGZQsfzuIKKZmZnZOKgOYEXEpMDSwGzAq8ADkl6JiLPKrYeVLdQtS/lSZx6ajQcHEmtqAZ6tgGPJhquTADdExG8lXS5pv4gYCewJrAu8BCxIlqJ5ufG1zOo8x8zMzMzMzMzMzMzGTwkGfhYRA4G/AjMBMwOfA89ExCaSHqsFEw+NiFGStnYQ0Wz8uEciY2WJrQBcB5wKPA70BY4GRgJnSBpa7tsEWBaYDLhF0mWNr2VW8RwzMzMzMzMzMzMz+/pKJuKdwAfA8cCjwKbADsA3gJUkPVHrmXgEcLikI1szYrOuzYHEmoiYCdgamB/YWdL/yvX5gfPIgM7uku5o5/m9JI1q0nCtC/IcMzMzMzMzMzMzMxs3ETEV8JGkkbVrqwMXApsDt5eypX3IpIwzgACWlvRB2Y9dE7jQpeTNxk+vVg+gsyhZYs8AmwAvSfpfpD6SngR2BeYBVmrvNRzgsY54jpmZmZmZmZmZmZmNm4hYEbgN+GbDQ3ORmYf/KEHEviVIeBdwLjA3sAiApNcknVfKobrVm9l4cCDxC38D7gAWBpaPiOlK+chRpe7yI2S69BoR0SciopWDtS7Jc8zMzMzMzMzMzMzsS0TEcsANwP3Aiw0PP1n+XR9A0shaMPEqYBKyb+IYnJFoNn56dCAxInqVf0PSB8CPgN8DSwMbR8RUkkaVUw2TA5MCL0j6zD3qbFx4jpmZmZmZmZmZmZmNuxJEvAU4E/iZpBENt7wGPATsGhGrwehgYm9gIeAV4OUmDtmsW+txqbwloFMFaAZExAigP/C+pPcjYmtgINmkdYaIOAfoBywPDAJ2acGwrQvxHDMzMzMzMzMzMzP76iJiaeAvwFDgcEmfREQvSaMiYhZJr0h6OiKOIQONJ0TE7MB1ZBDxYOB54J4W/Qlm3U70pKSneoAnIjYEdgDmA0YAvwL+JOk/ETEAuAJYA3gHeBr4vDx+XEsGb12C55iZmZmZmZmZmZnZVxcRUwF/Iqu5fUvSM6Ul1OcRsVh5bE9JV5T71wMOAJYqL/E68AywUpWhKOnz5v8lZt1LjwokViLiJ2TT1cuA4cAMwHrAH4AjJf0tIqYAzgY2AQ4kAzyPl+f7Dcg65DlmZmZmZmZmZmZmNu4iYlJyD/VYMvliI0kvlCDincAlwJ7A8FoyxxzALGQyxwvA7SXw2Mc9Ec0mjB4VSCz96uYB/ggMA46X9FF5bBvgPOB8YA9JH0fElMDlwGLkyYbLq/vN2uI5ZmZmZmZmZmZmZjZ+ImISYE3gdOBF4CiystulwF6SPi731dtLNb6GkzTMJqBerR7AxBQRi0fEDyJibQBJo4DpgZmBB2sBnl6SLgD2B7YFliz3vw9sDDwInARsHRH9mv+XWGflOWZmZmZmZmZmZmY2YUj6FLgB2J3cY/0TcA2waxVELPe1myHlIKLZhNVtA4kRcTxZVvI64NqIuDciZgD6ApMBfcp9fWpPu4JMmV65PNZL0ofAj8jaygtKGtG8v8I6M88xMzMzMzMzMzMzswmr7I/eAOwDPAXMD8zY0kGZ9WDdMpAYEecCWwNDgdXJmsrzA1cC/wCeBPYAkPRZySIDCLKf3X/LY6PKvx8Cy0naqXl/hXVmnmNmZmZmZmZmZmZmE0cJJl4PHERWgPtDRMzW2lGZ9Ux9vvyWriUizgLWJ8tF3inps4i4HxgBHAGsQ5aQ/HVEXAnsKOmd0sh1FWAS8pTDGCQNL6/fbu1l6xk8x8zMzMzMzMzMzMwmLknDI+L68uvpwO8jYn1Jr7RyXGY9TbcKJEbEqsAOwKWSbi3Xekv6KCJuBA4E3gX+AnyDPM3wYEQ8BnwO/AA4WtIt7f1vOMDTs3mOmZmZmZmZmZmZmTWHpE8j4gZgN7I63D0RsYSkN1s8NLMeo7uVNn2IzATbNCIOK9ei/DsnGTh9tzRlPRNYA3gUmA0YBews6RjI3nXNHLh1GZ5jZmZmZmZmZmZmZk1S65l4APAI8E5rR2TWs0R3S36KiIHA4cDewJGSDo+IxYA7gFMlHdLGc3qR/198Xv1e62lnNgbPMTMzMzMzMzMzM7Pmioi+kkaWn3tXe61mNnF1q9KmAJI+jIgh5ddDI2JmYFPgErJ/3egedFUwR9KoKjusPOYAj7XLc8zMzMzMzMzMzMysuaogYvnZQUSzJul2GYmVkjV2KFk7+RlgSUnDWzsq6048x8zMzMzMzMzMzMzMrDvrtj3aJH0IHEM2YP0OsH9rR2TdjeeYmZmZmZmZmZmZmZl1Z92utGmdpPci4ligL3B4RIySdGSrx2Xdh+eYmZmZmZmZmZmZmZl1V906kAgg6YPSz24UMDgiBkg6oNXjsu7Dc8zMzMzMzMzMzMzMzLqjbh9IhNGBnqOAyYFXWz0e6348x8zMzMzMzMzMzMzMrLsJSa0eQ9NExCSSPm31OKz78hwzMzMzMzMzMzMzM7PuokcFEs3MzMzMzMzMzMzMzMxs3PRq9QDMzMzMzMzMzMzMzMzMrPNxINHMzMzMzMzMzMzMzMzMxuJAopmZmZmZmZmZmZmZmZmNxYFEMzMzMzMzMzMzMzMzMxuLA4lmZmZmZmZmZmZmZmZmNhYHEs3MzMzMzMzMzMzMzMxsLA4kmpmZmZmZmZmZmZmZmdlYHEg0MzMzMzMzMzMzMzMzs7H8P7aGPWZr12O0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 2160x1296 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "msno.bar(df[missingdata_df], color=\"blue\", log=True, figsize=(30,18))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 552
    },
    "colab_type": "code",
    "id": "lyHg4w9aZEaQ",
    "outputId": "0d752fe9-524a-4e07-d600-600549ad1883"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Population_2011', 'Toilets', 'Female Pop', 'Hospitals', 'Foreign Visitors']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_4=dataset.iloc[0:787,[3,9,12,13,14]].values\n",
    "feat=['Population_2011','Toilets','Female Pop','Hospitals','Foreign Visitors']\n",
    "dtf=pd.DataFrame(X_4,columns=feat)\n",
    "missing_values_plot(dtf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "5ksSe6auZEaX"
   },
   "outputs": [],
   "source": [
    "#Dealing with Missing values\n",
    "def missing_values_handling(X_1,feat):\n",
    "    imp_mean=IterativeImputer(random_state=0)\n",
    "    X_T=imp_mean.fit_transform(X_1)\n",
    "\n",
    "    dtframe=pd.DataFrame(X_T,columns=feat)\n",
    "    train=dtframe\n",
    "    missing=train.isnull().sum()\n",
    "    total=train.count()\n",
    "    missing_df=pd.concat([missing,total],axis=1,keys=['Missing','All'])\n",
    "    print(missing_df)\n",
    "    return dtframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "9grnBTo8ZEac",
    "outputId": "067d505f-9eda-4508-9748-7a0f454c1ce5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  Missing  All\n",
      "Population_2011         0  787\n",
      "Toilets                 0  787\n",
      "Female Pop              0  787\n",
      "Hospitals               0  787\n",
      "Foreign Visitors        0  787\n"
     ]
    },
    {
     "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>Population_2011</th>\n",
       "      <th>Toilets</th>\n",
       "      <th>Female Pop</th>\n",
       "      <th>Hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12442373.0</td>\n",
       "      <td>219.000000</td>\n",
       "      <td>1.092440e+07</td>\n",
       "      <td>159.000000</td>\n",
       "      <td>4.408916e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11007835.0</td>\n",
       "      <td>215.000000</td>\n",
       "      <td>9.444722e+06</td>\n",
       "      <td>148.000000</td>\n",
       "      <td>2.379169e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8436675.0</td>\n",
       "      <td>212.000000</td>\n",
       "      <td>7.896728e+06</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>6.365020e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6809970.0</td>\n",
       "      <td>217.000000</td>\n",
       "      <td>6.333272e+06</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>1.260780e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5570585.0</td>\n",
       "      <td>227.000000</td>\n",
       "      <td>4.746138e+06</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>2.849730e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4681087.0</td>\n",
       "      <td>210.000000</td>\n",
       "      <td>4.231703e+06</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>4.684707e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4646732.0</td>\n",
       "      <td>145.000000</td>\n",
       "      <td>4.237820e+06</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>4.684707e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4486679.0</td>\n",
       "      <td>172.403104</td>\n",
       "      <td>4.239912e+06</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>1.489500e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4467797.0</td>\n",
       "      <td>159.527519</td>\n",
       "      <td>3.797627e+06</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>2.849730e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3124458.0</td>\n",
       "      <td>120.783114</td>\n",
       "      <td>2.743274e+06</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>4.408916e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>3046163.0</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>2.653208e+06</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>1.475311e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2817105.0</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>2.484687e+06</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>3.104060e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2800000.0</td>\n",
       "      <td>116.000000</td>\n",
       "      <td>2.573200e+06</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>4.213650e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2765348.0</td>\n",
       "      <td>135.000000</td>\n",
       "      <td>2.380965e+06</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>3.104060e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2405665.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.112174e+06</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>4.408916e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1964086.0</td>\n",
       "      <td>149.000000</td>\n",
       "      <td>1.824636e+06</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>4.213650e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1841488.0</td>\n",
       "      <td>119.000000</td>\n",
       "      <td>1.616826e+06</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>4.408916e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1798218.0</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>1.665150e+06</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>4.213650e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1728128.0</td>\n",
       "      <td>119.000000</td>\n",
       "      <td>1.539762e+06</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>2.378540e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1727692.0</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>1.506547e+06</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>4.408916e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1684222.0</td>\n",
       "      <td>142.000000</td>\n",
       "      <td>1.557905e+06</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>9.237370e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1670806.0</td>\n",
       "      <td>112.000000</td>\n",
       "      <td>1.403477e+06</td>\n",
       "      <td>91.000000</td>\n",
       "      <td>2.849730e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1648643.0</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>1.437617e+06</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>3.104060e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1618879.0</td>\n",
       "      <td>131.000000</td>\n",
       "      <td>1.406806e+06</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>2.423670e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1585704.0</td>\n",
       "      <td>124.000000</td>\n",
       "      <td>1.387491e+06</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>3.104060e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1486053.0</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>1.295838e+06</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>4.408916e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1456528.0</td>\n",
       "      <td>144.000000</td>\n",
       "      <td>1.303593e+06</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>1.677850e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1414050.0</td>\n",
       "      <td>127.000000</td>\n",
       "      <td>1.190630e+06</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>3.031180e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1305429.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.162061e+06</td>\n",
       "      <td>45.482561</td>\n",
       "      <td>1.611085e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1286678.0</td>\n",
       "      <td>129.000000</td>\n",
       "      <td>1.145415e+06</td>\n",
       "      <td>66.882574</td>\n",
       "      <td>1.608212e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1247327.0</td>\n",
       "      <td>144.000000</td>\n",
       "      <td>1.110479e+06</td>\n",
       "      <td>77.927175</td>\n",
       "      <td>1.602183e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1222390.0</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>1.088340e+06</td>\n",
       "      <td>74.952826</td>\n",
       "      <td>1.598361e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1201815.0</td>\n",
       "      <td>121.000000</td>\n",
       "      <td>1.070073e+06</td>\n",
       "      <td>60.905119</td>\n",
       "      <td>1.595209e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1180570.0</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>1.051211e+06</td>\n",
       "      <td>56.456879</td>\n",
       "      <td>1.591953e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Population_2011     Toilets    Female Pop   Hospitals  Foreign Visitors\n",
       "0        12442373.0  219.000000  1.092440e+07  159.000000      4.408916e+06\n",
       "1        11007835.0  215.000000  9.444722e+06  148.000000      2.379169e+06\n",
       "2         8436675.0  212.000000  7.896728e+06  123.000000      6.365020e+05\n",
       "3         6809970.0  217.000000  6.333272e+06  110.000000      1.260780e+05\n",
       "4         5570585.0  227.000000  4.746138e+06   73.000000      2.849730e+05\n",
       "5         4681087.0  210.000000  4.231703e+06   67.000000      4.684707e+06\n",
       "6         4646732.0  145.000000  4.237820e+06   55.000000      4.684707e+06\n",
       "7         4486679.0  172.403104  4.239912e+06   82.000000      1.489500e+06\n",
       "8         4467797.0  159.527519  3.797627e+06   98.000000      2.849730e+05\n",
       "9         3124458.0  120.783114  2.743274e+06   50.000000      4.408916e+06\n",
       "10        3046163.0  128.000000  2.653208e+06   61.000000      1.475311e+06\n",
       "11        2817105.0  123.000000  2.484687e+06   58.000000      3.104060e+06\n",
       "12        2800000.0  116.000000  2.573200e+06   56.000000      4.213650e+05\n",
       "13        2765348.0  135.000000  2.380965e+06   94.000000      3.104060e+06\n",
       "14        2405665.0  100.000000  2.112174e+06   52.000000      4.408916e+06\n",
       "15        1964086.0  149.000000  1.824636e+06   76.000000      4.213650e+05\n",
       "16        1841488.0  119.000000  1.616826e+06   90.000000      4.408916e+06\n",
       "17        1798218.0  113.000000  1.665150e+06   72.000000      4.213650e+05\n",
       "18        1728128.0  119.000000  1.539762e+06   51.000000      2.378540e+05\n",
       "19        1727692.0  108.000000  1.506547e+06   93.000000      4.408916e+06\n",
       "20        1684222.0  142.000000  1.557905e+06   62.000000      9.237370e+05\n",
       "21        1670806.0  112.000000  1.403477e+06   91.000000      2.849730e+05\n",
       "22        1648643.0  122.000000  1.437617e+06   72.000000      3.104060e+06\n",
       "23        1618879.0  131.000000  1.406806e+06   73.000000      2.423670e+05\n",
       "24        1585704.0  124.000000  1.387491e+06   99.000000      3.104060e+06\n",
       "25        1486053.0  122.000000  1.295838e+06   66.000000      4.408916e+06\n",
       "26        1456528.0  144.000000  1.303593e+06   59.000000      1.677850e+05\n",
       "27        1414050.0  127.000000  1.190630e+06   59.000000      3.031180e+05\n",
       "28        1305429.0  100.000000  1.162061e+06   45.482561      1.611085e+06\n",
       "29        1286678.0  129.000000  1.145415e+06   66.882574      1.608212e+06\n",
       "30        1247327.0  144.000000  1.110479e+06   77.927175      1.602183e+06\n",
       "31        1222390.0  140.000000  1.088340e+06   74.952826      1.598361e+06\n",
       "32        1201815.0  121.000000  1.070073e+06   60.905119      1.595209e+06\n",
       "33        1180570.0  115.000000  1.051211e+06   56.456879      1.591953e+06"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_1=dataset.iloc[0:787,[3,9,12,13,14]].values\n",
    "feat=feat\n",
    "final_df=missing_values_handling(X_1,feat)\n",
    "final_df.head(34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 603
    },
    "colab_type": "code",
    "id": "8dT3h3sWZEah",
    "outputId": "6702891c-1457-4895-bc6e-a29d50b4984f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  Missing  All\n",
      "Population_2011         0  787\n",
      "Population_2001         0  787\n",
      "Sex Ratio               0  787\n",
      "Median Age              0  787\n",
      "Avg Temp                0  787\n",
      "Toilets                 0  787\n",
      "Water Purity            0  787\n",
      "H index                 0  787\n",
      "Female Pop              0  787\n",
      "Hospitals               0  787\n",
      "Foreign Visitors        0  787\n"
     ]
    },
    {
     "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>Population_2011</th>\n",
       "      <th>Population_2001</th>\n",
       "      <th>Sex Ratio</th>\n",
       "      <th>Median Age</th>\n",
       "      <th>Avg Temp</th>\n",
       "      <th>Toilets</th>\n",
       "      <th>Water Purity</th>\n",
       "      <th>H index</th>\n",
       "      <th>Female Pop</th>\n",
       "      <th>Hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12442373.0</td>\n",
       "      <td>1.197845e+07</td>\n",
       "      <td>878.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.700440</td>\n",
       "      <td>10924403.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>4408916.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11007835.0</td>\n",
       "      <td>9.879172e+06</td>\n",
       "      <td>858.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>0.920018</td>\n",
       "      <td>9444722.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>2379169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8436675.0</td>\n",
       "      <td>4.301326e+06</td>\n",
       "      <td>936.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>0.097085</td>\n",
       "      <td>7896728.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>636502.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6809970.0</td>\n",
       "      <td>3.637483e+06</td>\n",
       "      <td>930.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>0.827744</td>\n",
       "      <td>6333272.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>126078.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5570585.0</td>\n",
       "      <td>3.520085e+06</td>\n",
       "      <td>852.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>227.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>0.847941</td>\n",
       "      <td>4746138.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>284973.0</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>782</th>\n",
       "      <td>36954.0</td>\n",
       "      <td>1.123028e+04</td>\n",
       "      <td>846.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>0.035280</td>\n",
       "      <td>31263.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>284973.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>783</th>\n",
       "      <td>36947.0</td>\n",
       "      <td>2.471994e+04</td>\n",
       "      <td>945.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>0.056394</td>\n",
       "      <td>34915.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1489500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>784</th>\n",
       "      <td>36828.0</td>\n",
       "      <td>-6.018899e+03</td>\n",
       "      <td>1019.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>0.066752</td>\n",
       "      <td>37528.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>106153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>785</th>\n",
       "      <td>36805.0</td>\n",
       "      <td>2.101883e+03</td>\n",
       "      <td>900.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>0.627556</td>\n",
       "      <td>33125.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>24720.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>36776.0</td>\n",
       "      <td>5.793478e+04</td>\n",
       "      <td>889.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>0.313383</td>\n",
       "      <td>32694.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3104060.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>787 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Population_2011  Population_2001  Sex Ratio  Median Age  Avg Temp  \\\n",
       "0         12442373.0     1.197845e+07      878.0        23.0      32.0   \n",
       "1         11007835.0     9.879172e+06      858.0        27.0      30.0   \n",
       "2          8436675.0     4.301326e+06      936.0        28.0      37.0   \n",
       "3          6809970.0     3.637483e+06      930.0        23.0      31.0   \n",
       "4          5570585.0     3.520085e+06      852.0        29.0      25.0   \n",
       "..               ...              ...        ...         ...       ...   \n",
       "782          36954.0     1.123028e+04      846.0        23.0      28.0   \n",
       "783          36947.0     2.471994e+04      945.0        23.0      36.0   \n",
       "784          36828.0    -6.018899e+03     1019.0        28.0      28.0   \n",
       "785          36805.0     2.101883e+03      900.0        24.0       6.0   \n",
       "786          36776.0     5.793478e+04      889.0        25.0      37.0   \n",
       "\n",
       "     Toilets  Water Purity   H index  Female Pop  Hospitals  Foreign Visitors  \n",
       "0      219.0         150.0  0.700440  10924403.0      159.0         4408916.0  \n",
       "1      215.0         196.0  0.920018   9444722.0      148.0         2379169.0  \n",
       "2      212.0         102.0  0.097085   7896728.0      123.0          636502.0  \n",
       "3      217.0         118.0  0.827744   6333272.0      110.0          126078.0  \n",
       "4      227.0         109.0  0.847941   4746138.0       73.0          284973.0  \n",
       "..       ...           ...       ...         ...        ...               ...  \n",
       "782     68.0         103.0  0.035280     31263.0       19.0          284973.0  \n",
       "783     62.0         136.0  0.056394     34915.0       22.0         1489500.0  \n",
       "784     98.0         138.0  0.066752     37528.0       27.0          106153.0  \n",
       "785     63.0         145.0  0.627556     33125.0       15.0           24720.0  \n",
       "786     51.0         181.0  0.313383     32694.0       30.0         3104060.0  \n",
       "\n",
       "[787 rows x 11 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prefinal_df=missing_values_handling(X,features)\n",
    "prefinal_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Principal Component Analysis & Correlation Circle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "qMio-UC5ZEan"
   },
   "outputs": [],
   "source": [
    "def pca_analysis(X):\n",
    "    sc_X=StandardScaler()\n",
    "    X_scale=sc_X.fit_transform(X)\n",
    "    \n",
    "    pca=PCA()\n",
    "    X_pca=pca.fit_transform(X_scale)\n",
    "    explained_variance=pca.explained_variance_ratio_\n",
    "    print(explained_variance)\n",
    "    \n",
    "def correlation_circle(X,labels):\n",
    "    plot_pca_correlation_graph(X,labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 67
    },
    "colab_type": "code",
    "id": "BSf4ikDOZzoE",
    "outputId": "9a78ad62-6c60-4559-8334-c31789d0eed0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.34043996e-01 1.14946665e-01 1.03915149e-01 1.00005155e-01\n",
      " 9.18849480e-02 8.81119539e-02 8.07009240e-02 6.48233112e-02\n",
      " 1.82810883e-02 3.24554126e-03 4.12676499e-05]\n"
     ]
    }
   ],
   "source": [
    "X_tr=prefinal_df.to_numpy()\n",
    "pca_analysis(X_tr)\n",
    "\n",
    "correlation_circle(X_tr,features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 50
    },
    "colab_type": "code",
    "id": "kEzOYBFIZ-Dd",
    "outputId": "7d5b2de2-dde9-48d4-96ee-ba672b6218b4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.67630260e-01 2.01732499e-01 1.89924057e-01 4.05792359e-02\n",
      " 1.33948087e-04]\n"
     ]
    }
   ],
   "source": [
    "X_final=final_df.to_numpy()\n",
    "pca_analysis(X_final)\n",
    "\n",
    "correlation_circle(X_final,feat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "wK6RuITpZEa7"
   },
   "outputs": [],
   "source": [
    "X_final=np.delete(X_final,[7,8,9,665],0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 402
    },
    "colab_type": "code",
    "id": "HUQKVB_BZEbC",
    "outputId": "461fae85-37a8-4b5e-e4d5-287c127d5292"
   },
   "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>Population_2011</th>\n",
       "      <th>Toilets</th>\n",
       "      <th>Female Pop</th>\n",
       "      <th>Hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12442373.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>10924403.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>4408916.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11007835.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>9444722.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>2379169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8436675.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>7896728.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>636502.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6809970.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>6333272.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>126078.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5570585.0</td>\n",
       "      <td>227.0</td>\n",
       "      <td>4746138.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>284973.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>36954.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>31263.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>284973.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>779</th>\n",
       "      <td>36947.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>34915.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1489500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>780</th>\n",
       "      <td>36828.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>37528.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>106153.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>781</th>\n",
       "      <td>36805.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>33125.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>24720.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\n",
       "      <td>36776.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>32694.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3104060.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>783 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Population_2011  Toilets  Female Pop  Hospitals  Foreign Visitors\n",
       "0         12442373.0    219.0  10924403.0      159.0         4408916.0\n",
       "1         11007835.0    215.0   9444722.0      148.0         2379169.0\n",
       "2          8436675.0    212.0   7896728.0      123.0          636502.0\n",
       "3          6809970.0    217.0   6333272.0      110.0          126078.0\n",
       "4          5570585.0    227.0   4746138.0       73.0          284973.0\n",
       "..               ...      ...         ...        ...               ...\n",
       "778          36954.0     68.0     31263.0       19.0          284973.0\n",
       "779          36947.0     62.0     34915.0       22.0         1489500.0\n",
       "780          36828.0     98.0     37528.0       27.0          106153.0\n",
       "781          36805.0     63.0     33125.0       15.0           24720.0\n",
       "782          36776.0     51.0     32694.0       30.0         3104060.0\n",
       "\n",
       "[783 rows x 5 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Fn_df=pd.DataFrame(X_final,columns=feat)\n",
    "Fn_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conversion of Categorical Variables "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 472
    },
    "colab_type": "code",
    "id": "i1J9Qh5oZEbJ",
    "outputId": "ef5f031a-74bf-4f22-9cd0-23b0ba321fdb"
   },
   "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>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Type</th>\n",
       "      <th>Population [2011]</th>\n",
       "      <th>Popuation [2001]</th>\n",
       "      <th>Sex Ratio</th>\n",
       "      <th>Median Age</th>\n",
       "      <th>Avg Temp</th>\n",
       "      <th>SWM</th>\n",
       "      <th>Toilets Avl</th>\n",
       "      <th>Water Purity</th>\n",
       "      <th>H Index</th>\n",
       "      <th>Female Population</th>\n",
       "      <th># of hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "      <th>Covid Cases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>M.C</td>\n",
       "      <td>12442373.0</td>\n",
       "      <td>11978450.0</td>\n",
       "      <td>878.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>219.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.700440</td>\n",
       "      <td>10924403.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>4408916.0</td>\n",
       "      <td>163115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>M.C</td>\n",
       "      <td>11007835.0</td>\n",
       "      <td>9879172.0</td>\n",
       "      <td>858.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>215.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>0.920018</td>\n",
       "      <td>9444722.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>2379169.0</td>\n",
       "      <td>80188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>8436675.0</td>\n",
       "      <td>4301326.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>212.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>0.097085</td>\n",
       "      <td>7896728.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>636502.0</td>\n",
       "      <td>141000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>6809970.0</td>\n",
       "      <td>3637483.0</td>\n",
       "      <td>930.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>217.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>0.827744</td>\n",
       "      <td>6333272.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>126078.0</td>\n",
       "      <td>55123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>5570585.0</td>\n",
       "      <td>3520085.0</td>\n",
       "      <td>852.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>LOW</td>\n",
       "      <td>227.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>0.847941</td>\n",
       "      <td>4746138.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>284973.0</td>\n",
       "      <td>33204</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\n",
       "      <td>Lunawada</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>M</td>\n",
       "      <td>36954.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>846.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>68.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>0.035280</td>\n",
       "      <td>31263.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>284973.0</td>\n",
       "      <td>1944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>783</th>\n",
       "      <td>Murshidabad</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>M</td>\n",
       "      <td>36947.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>945.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>62.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>0.056394</td>\n",
       "      <td>34915.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1489500.0</td>\n",
       "      <td>2172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>784</th>\n",
       "      <td>Mahe</td>\n",
       "      <td>Puducherry</td>\n",
       "      <td>M</td>\n",
       "      <td>36828.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1019.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>98.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>0.066752</td>\n",
       "      <td>37528.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>106153.0</td>\n",
       "      <td>2851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>785</th>\n",
       "      <td>Lanka</td>\n",
       "      <td>Assam</td>\n",
       "      <td>M.B</td>\n",
       "      <td>36805.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>900.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>63.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>0.627556</td>\n",
       "      <td>33125.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>24720.0</td>\n",
       "      <td>2158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>Rudauli</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>M.B</td>\n",
       "      <td>36776.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>889.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>51.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>0.313383</td>\n",
       "      <td>32694.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3104060.0</td>\n",
       "      <td>2220</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>787 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            City          State  Type  Population [2011]  Popuation [2001]  \\\n",
       "0         Mumbai    Maharashtra   M.C         12442373.0        11978450.0   \n",
       "1          Delhi          Delhi   M.C         11007835.0         9879172.0   \n",
       "2      Bangalore      Karnataka  MPUA          8436675.0         4301326.0   \n",
       "3      Hyderabad      Telangana  MPUA          6809970.0         3637483.0   \n",
       "4      Ahmedabad        Gujarat  MPUA          5570585.0         3520085.0   \n",
       "..           ...            ...   ...                ...               ...   \n",
       "782     Lunawada        Gujarat     M            36954.0               NaN   \n",
       "783  Murshidabad    West Bengal     M            36947.0               NaN   \n",
       "784         Mahe     Puducherry     M            36828.0               NaN   \n",
       "785        Lanka          Assam   M.B            36805.0               NaN   \n",
       "786      Rudauli  Uttar Pradesh   M.B            36776.0               NaN   \n",
       "\n",
       "     Sex Ratio  Median Age  Avg Temp     SWM  Toilets Avl  Water Purity  \\\n",
       "0        878.0        23.0      32.0  MEDIUM        219.0         150.0   \n",
       "1        858.0        27.0      30.0  MEDIUM        215.0         196.0   \n",
       "2        936.0        28.0      37.0    HIGH        212.0         102.0   \n",
       "3        930.0        23.0      31.0  MEDIUM        217.0         118.0   \n",
       "4        852.0        29.0      25.0     LOW        227.0         109.0   \n",
       "..         ...         ...       ...     ...          ...           ...   \n",
       "782      846.0        23.0      28.0  MEDIUM         68.0         103.0   \n",
       "783      945.0        23.0      36.0  MEDIUM         62.0         136.0   \n",
       "784     1019.0        28.0      28.0    HIGH         98.0         138.0   \n",
       "785      900.0        24.0       6.0  MEDIUM         63.0         145.0   \n",
       "786      889.0        25.0      37.0    HIGH         51.0         181.0   \n",
       "\n",
       "      H Index  Female Population  # of hospitals  Foreign Visitors  \\\n",
       "0    0.700440         10924403.0           159.0         4408916.0   \n",
       "1    0.920018          9444722.0           148.0         2379169.0   \n",
       "2    0.097085          7896728.0           123.0          636502.0   \n",
       "3    0.827744          6333272.0           110.0          126078.0   \n",
       "4    0.847941          4746138.0            73.0          284973.0   \n",
       "..        ...                ...             ...               ...   \n",
       "782  0.035280            31263.0            19.0          284973.0   \n",
       "783  0.056394            34915.0            22.0         1489500.0   \n",
       "784  0.066752            37528.0            27.0          106153.0   \n",
       "785  0.627556            33125.0            15.0           24720.0   \n",
       "786  0.313383            32694.0            30.0         3104060.0   \n",
       "\n",
       "     Covid Cases  \n",
       "0         163115  \n",
       "1          80188  \n",
       "2         141000  \n",
       "3          55123  \n",
       "4          33204  \n",
       "..           ...  \n",
       "782         1944  \n",
       "783         2172  \n",
       "784         2851  \n",
       "785         2158  \n",
       "786         2220  \n",
       "\n",
       "[787 rows x 16 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "gTR4xO-MZEbR"
   },
   "outputs": [],
   "source": [
    "X_cat=df_cat.to_numpy()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "KcLyyweGZEbb"
   },
   "outputs": [],
   "source": [
    "X_cat=np.delete(X_cat,[7,8,9,665],0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hC6-hjyGZEbg"
   },
   "outputs": [],
   "source": [
    "df_cat_1 = pd.DataFrame(data=X_cat, columns=[\"City\", \"State\", \"Type\", \"Population [2011]\", \"Popuation [2001]\", \"Sex Ratio\", \"Median Age\", \"Avg Temp\", \"SWM\", \"Toilets Avl\", \"Water Purity\", \"H Index\", \"Female Population\", \"# of hospitals\", \"Foreign Visitors\", \"Covid Cases\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 612
    },
    "colab_type": "code",
    "id": "aauYaKwbZEbl",
    "outputId": "7e55c181-4261-4efe-ccc2-c71a3ae8f6fd"
   },
   "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>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Type</th>\n",
       "      <th>Population [2011]</th>\n",
       "      <th>Popuation [2001]</th>\n",
       "      <th>Sex Ratio</th>\n",
       "      <th>Median Age</th>\n",
       "      <th>Avg Temp</th>\n",
       "      <th>SWM</th>\n",
       "      <th>Toilets Avl</th>\n",
       "      <th>Water Purity</th>\n",
       "      <th>H Index</th>\n",
       "      <th>Female Population</th>\n",
       "      <th># of hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "      <th>Covid Cases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>M.C</td>\n",
       "      <td>1.24424e+07</td>\n",
       "      <td>1.19784e+07</td>\n",
       "      <td>878</td>\n",
       "      <td>23</td>\n",
       "      <td>32</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>219</td>\n",
       "      <td>150</td>\n",
       "      <td>0.70044</td>\n",
       "      <td>1.09244e+07</td>\n",
       "      <td>159</td>\n",
       "      <td>4.40892e+06</td>\n",
       "      <td>163115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>M.C</td>\n",
       "      <td>1.10078e+07</td>\n",
       "      <td>9.87917e+06</td>\n",
       "      <td>858</td>\n",
       "      <td>27</td>\n",
       "      <td>30</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>215</td>\n",
       "      <td>196</td>\n",
       "      <td>0.920018</td>\n",
       "      <td>9.44472e+06</td>\n",
       "      <td>148</td>\n",
       "      <td>2.37917e+06</td>\n",
       "      <td>80188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>8.43668e+06</td>\n",
       "      <td>4.30133e+06</td>\n",
       "      <td>936</td>\n",
       "      <td>28</td>\n",
       "      <td>37</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>212</td>\n",
       "      <td>102</td>\n",
       "      <td>0.0970853</td>\n",
       "      <td>7.89673e+06</td>\n",
       "      <td>123</td>\n",
       "      <td>636502</td>\n",
       "      <td>141000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>6.80997e+06</td>\n",
       "      <td>3.63748e+06</td>\n",
       "      <td>930</td>\n",
       "      <td>23</td>\n",
       "      <td>31</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>217</td>\n",
       "      <td>118</td>\n",
       "      <td>0.827744</td>\n",
       "      <td>6.33327e+06</td>\n",
       "      <td>110</td>\n",
       "      <td>126078</td>\n",
       "      <td>55123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>5.57058e+06</td>\n",
       "      <td>3.52008e+06</td>\n",
       "      <td>852</td>\n",
       "      <td>29</td>\n",
       "      <td>25</td>\n",
       "      <td>LOW</td>\n",
       "      <td>227</td>\n",
       "      <td>109</td>\n",
       "      <td>0.847941</td>\n",
       "      <td>4.74614e+06</td>\n",
       "      <td>73</td>\n",
       "      <td>284973</td>\n",
       "      <td>33204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Chennai</td>\n",
       "      <td>Tamil Nadu</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>4.68109e+06</td>\n",
       "      <td>4.34364e+06</td>\n",
       "      <td>904</td>\n",
       "      <td>26</td>\n",
       "      <td>31</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>210</td>\n",
       "      <td>179</td>\n",
       "      <td>0.536995</td>\n",
       "      <td>4.2317e+06</td>\n",
       "      <td>67</td>\n",
       "      <td>4.68471e+06</td>\n",
       "      <td>145606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Chennai</td>\n",
       "      <td>Tamil nadu</td>\n",
       "      <td>T</td>\n",
       "      <td>4.64673e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>912</td>\n",
       "      <td>26</td>\n",
       "      <td>30</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>145</td>\n",
       "      <td>177</td>\n",
       "      <td>0.0934507</td>\n",
       "      <td>4.23782e+06</td>\n",
       "      <td>55</td>\n",
       "      <td>4.68471e+06</td>\n",
       "      <td>145606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Jaipur</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>3.04616e+06</td>\n",
       "      <td>2.32258e+06</td>\n",
       "      <td>871</td>\n",
       "      <td>26</td>\n",
       "      <td>32</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>128</td>\n",
       "      <td>172</td>\n",
       "      <td>0.889895</td>\n",
       "      <td>2.65321e+06</td>\n",
       "      <td>61</td>\n",
       "      <td>1.47531e+06</td>\n",
       "      <td>14001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Lucknow</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>2.81710e+06</td>\n",
       "      <td>2.18593e+06</td>\n",
       "      <td>882</td>\n",
       "      <td>24</td>\n",
       "      <td>33</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>123</td>\n",
       "      <td>176</td>\n",
       "      <td>0.464746</td>\n",
       "      <td>2.48469e+06</td>\n",
       "      <td>58</td>\n",
       "      <td>3.10406e+06</td>\n",
       "      <td>37220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Indore</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>M</td>\n",
       "      <td>2.8e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>919</td>\n",
       "      <td>25</td>\n",
       "      <td>34</td>\n",
       "      <td>LOW</td>\n",
       "      <td>116</td>\n",
       "      <td>142</td>\n",
       "      <td>0.815466</td>\n",
       "      <td>2.5732e+06</td>\n",
       "      <td>56</td>\n",
       "      <td>421365</td>\n",
       "      <td>15764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Kanpur</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>2.76535e+06</td>\n",
       "      <td>2.55134e+06</td>\n",
       "      <td>861</td>\n",
       "      <td>26</td>\n",
       "      <td>29</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>135</td>\n",
       "      <td>122</td>\n",
       "      <td>0.053147</td>\n",
       "      <td>2.38096e+06</td>\n",
       "      <td>94</td>\n",
       "      <td>3.10406e+06</td>\n",
       "      <td>22413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Nagpur</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>2.40566e+06</td>\n",
       "      <td>2.05207e+06</td>\n",
       "      <td>878</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>100</td>\n",
       "      <td>136</td>\n",
       "      <td>0.0107301</td>\n",
       "      <td>2.11217e+06</td>\n",
       "      <td>52</td>\n",
       "      <td>4.40892e+06</td>\n",
       "      <td>44700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Indore</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>1.96409e+06</td>\n",
       "      <td>1.47497e+06</td>\n",
       "      <td>929</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>149</td>\n",
       "      <td>172</td>\n",
       "      <td>0.884344</td>\n",
       "      <td>1.82464e+06</td>\n",
       "      <td>76</td>\n",
       "      <td>421365</td>\n",
       "      <td>15764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Thane</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>1.84149e+06</td>\n",
       "      <td>1.26255e+06</td>\n",
       "      <td>878</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32</td>\n",
       "      <td>LOW</td>\n",
       "      <td>119</td>\n",
       "      <td>199</td>\n",
       "      <td>0.727836</td>\n",
       "      <td>1.61683e+06</td>\n",
       "      <td>90</td>\n",
       "      <td>4.40892e+06</td>\n",
       "      <td>150793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Bhopal</td>\n",
       "      <td>Madhya Pradesh</td>\n",
       "      <td>MPUA</td>\n",
       "      <td>1.79822e+06</td>\n",
       "      <td>1.43735e+06</td>\n",
       "      <td>926</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>LOW</td>\n",
       "      <td>113</td>\n",
       "      <td>185</td>\n",
       "      <td>0.333171</td>\n",
       "      <td>1.66515e+06</td>\n",
       "      <td>72</td>\n",
       "      <td>421365</td>\n",
       "      <td>12446</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         City           State  Type Population [2011] Popuation [2001]  \\\n",
       "0      Mumbai     Maharashtra   M.C       1.24424e+07      1.19784e+07   \n",
       "1       Delhi           Delhi   M.C       1.10078e+07      9.87917e+06   \n",
       "2   Bangalore       Karnataka  MPUA       8.43668e+06      4.30133e+06   \n",
       "3   Hyderabad       Telangana  MPUA       6.80997e+06      3.63748e+06   \n",
       "4   Ahmedabad         Gujarat  MPUA       5.57058e+06      3.52008e+06   \n",
       "5     Chennai      Tamil Nadu  MPUA       4.68109e+06      4.34364e+06   \n",
       "6     Chennai      Tamil nadu     T       4.64673e+06              NaN   \n",
       "7      Jaipur       Rajasthan  MPUA       3.04616e+06      2.32258e+06   \n",
       "8     Lucknow   Uttar Pradesh  MPUA       2.81710e+06      2.18593e+06   \n",
       "9      Indore  Madhya Pradesh     M           2.8e+06              NaN   \n",
       "10     Kanpur   Uttar Pradesh  MPUA       2.76535e+06      2.55134e+06   \n",
       "11     Nagpur     Maharashtra  MPUA       2.40566e+06      2.05207e+06   \n",
       "12     Indore  Madhya Pradesh  MPUA       1.96409e+06      1.47497e+06   \n",
       "13      Thane     Maharashtra  MPUA       1.84149e+06      1.26255e+06   \n",
       "14     Bhopal  Madhya Pradesh  MPUA       1.79822e+06      1.43735e+06   \n",
       "\n",
       "   Sex Ratio Median Age Avg Temp     SWM Toilets Avl Water Purity    H Index  \\\n",
       "0        878         23       32  MEDIUM         219          150    0.70044   \n",
       "1        858         27       30  MEDIUM         215          196   0.920018   \n",
       "2        936         28       37    HIGH         212          102  0.0970853   \n",
       "3        930         23       31  MEDIUM         217          118   0.827744   \n",
       "4        852         29       25     LOW         227          109   0.847941   \n",
       "5        904         26       31    HIGH         210          179   0.536995   \n",
       "6        912         26       30  MEDIUM         145          177  0.0934507   \n",
       "7        871         26       32    HIGH         128          172   0.889895   \n",
       "8        882         24       33    HIGH         123          176   0.464746   \n",
       "9        919         25       34     LOW         116          142   0.815466   \n",
       "10       861         26       29    HIGH         135          122   0.053147   \n",
       "11       878        NaN       35  MEDIUM         100          136  0.0107301   \n",
       "12       929        NaN       37  MEDIUM         149          172   0.884344   \n",
       "13       878        NaN       32     LOW         119          199   0.727836   \n",
       "14       926        NaN       35     LOW         113          185   0.333171   \n",
       "\n",
       "   Female Population # of hospitals Foreign Visitors Covid Cases  \n",
       "0        1.09244e+07            159      4.40892e+06      163115  \n",
       "1        9.44472e+06            148      2.37917e+06       80188  \n",
       "2        7.89673e+06            123           636502      141000  \n",
       "3        6.33327e+06            110           126078       55123  \n",
       "4        4.74614e+06             73           284973       33204  \n",
       "5         4.2317e+06             67      4.68471e+06      145606  \n",
       "6        4.23782e+06             55      4.68471e+06      145606  \n",
       "7        2.65321e+06             61      1.47531e+06       14001  \n",
       "8        2.48469e+06             58      3.10406e+06       37220  \n",
       "9         2.5732e+06             56           421365       15764  \n",
       "10       2.38096e+06             94      3.10406e+06       22413  \n",
       "11       2.11217e+06             52      4.40892e+06       44700  \n",
       "12       1.82464e+06             76           421365       15764  \n",
       "13       1.61683e+06             90      4.40892e+06      150793  \n",
       "14       1.66515e+06             72           421365       12446  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat_1.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "mhTZCk0MZEbo"
   },
   "outputs": [],
   "source": [
    "df_cat_1['Type']=df_cat_1['Type'].replace(['M.B','N.P.P',              \n",
    "'T.M.C',              \n",
    "'N.P',             \n",
    "'C.T',             \n",
    "'M.Cl.',               \n",
    "'C.M.C',               \n",
    "'M.C',                 \n",
    "'N.A.C',               \n",
    "'N.P.P.',              \n",
    "'T.P',                 \n",
    "'NP',                  \n",
    "'C.B',                 \n",
    "'T.M.C.',              \n",
    "'CMC',                 \n",
    "'N.Pd',                \n",
    "'M.B.',                \n",
    "'N.P.',                \n",
    "'N.A',                 \n",
    "'T',                  \n",
    "'MB',                  \n",
    "'M.Corp',              \n",
    "'NPP',               \n",
    "'T.C',                 \n",
    "'C.T.',                \n",
    "'Nagar Parishad',      \n",
    "'M.Corp.',             \n",
    "'M Cl',                \n",
    "'N.T',                 \n",
    "'U.A',                 \n",
    "'T.P.',                \n",
    "'Np'], 'UA')\n",
    "\n",
    "dummies = pd.get_dummies(df_cat_1['Type'],drop_first=True)\n",
    "df_cat_1 = df_cat_1.drop('Type',axis=1)\n",
    "df_cat_1 = pd.concat([df_cat_1,dummies],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 232
    },
    "colab_type": "code",
    "id": "rYAUg0IGZEbr",
    "outputId": "e387c4b5-e83b-4968-9403-35593ab62978"
   },
   "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>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Population [2011]</th>\n",
       "      <th>Popuation [2001]</th>\n",
       "      <th>Sex Ratio</th>\n",
       "      <th>Median Age</th>\n",
       "      <th>Avg Temp</th>\n",
       "      <th>SWM</th>\n",
       "      <th>Toilets Avl</th>\n",
       "      <th>Water Purity</th>\n",
       "      <th>H Index</th>\n",
       "      <th>Female Population</th>\n",
       "      <th># of hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "      <th>Covid Cases</th>\n",
       "      <th>M</th>\n",
       "      <th>M.Cl</th>\n",
       "      <th>MPUA</th>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>1.24424e+07</td>\n",
       "      <td>1.19784e+07</td>\n",
       "      <td>878</td>\n",
       "      <td>23</td>\n",
       "      <td>32</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>219</td>\n",
       "      <td>150</td>\n",
       "      <td>0.70044</td>\n",
       "      <td>1.09244e+07</td>\n",
       "      <td>159</td>\n",
       "      <td>4.40892e+06</td>\n",
       "      <td>163115</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Delhi</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>1.10078e+07</td>\n",
       "      <td>9.87917e+06</td>\n",
       "      <td>858</td>\n",
       "      <td>27</td>\n",
       "      <td>30</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>215</td>\n",
       "      <td>196</td>\n",
       "      <td>0.920018</td>\n",
       "      <td>9.44472e+06</td>\n",
       "      <td>148</td>\n",
       "      <td>2.37917e+06</td>\n",
       "      <td>80188</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bangalore</td>\n",
       "      <td>Karnataka</td>\n",
       "      <td>8.43668e+06</td>\n",
       "      <td>4.30133e+06</td>\n",
       "      <td>936</td>\n",
       "      <td>28</td>\n",
       "      <td>37</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>212</td>\n",
       "      <td>102</td>\n",
       "      <td>0.0970853</td>\n",
       "      <td>7.89673e+06</td>\n",
       "      <td>123</td>\n",
       "      <td>636502</td>\n",
       "      <td>141000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>6.80997e+06</td>\n",
       "      <td>3.63748e+06</td>\n",
       "      <td>930</td>\n",
       "      <td>23</td>\n",
       "      <td>31</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>217</td>\n",
       "      <td>118</td>\n",
       "      <td>0.827744</td>\n",
       "      <td>6.33327e+06</td>\n",
       "      <td>110</td>\n",
       "      <td>126078</td>\n",
       "      <td>55123</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>5.57058e+06</td>\n",
       "      <td>3.52008e+06</td>\n",
       "      <td>852</td>\n",
       "      <td>29</td>\n",
       "      <td>25</td>\n",
       "      <td>LOW</td>\n",
       "      <td>227</td>\n",
       "      <td>109</td>\n",
       "      <td>0.847941</td>\n",
       "      <td>4.74614e+06</td>\n",
       "      <td>73</td>\n",
       "      <td>284973</td>\n",
       "      <td>33204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        City        State Population [2011] Popuation [2001] Sex Ratio  \\\n",
       "0     Mumbai  Maharashtra       1.24424e+07      1.19784e+07       878   \n",
       "1      Delhi        Delhi       1.10078e+07      9.87917e+06       858   \n",
       "2  Bangalore    Karnataka       8.43668e+06      4.30133e+06       936   \n",
       "3  Hyderabad    Telangana       6.80997e+06      3.63748e+06       930   \n",
       "4  Ahmedabad      Gujarat       5.57058e+06      3.52008e+06       852   \n",
       "\n",
       "  Median Age Avg Temp     SWM Toilets Avl Water Purity    H Index  \\\n",
       "0         23       32  MEDIUM         219          150    0.70044   \n",
       "1         27       30  MEDIUM         215          196   0.920018   \n",
       "2         28       37    HIGH         212          102  0.0970853   \n",
       "3         23       31  MEDIUM         217          118   0.827744   \n",
       "4         29       25     LOW         227          109   0.847941   \n",
       "\n",
       "  Female Population # of hospitals Foreign Visitors Covid Cases  M  M.Cl  \\\n",
       "0       1.09244e+07            159      4.40892e+06      163115  0     0   \n",
       "1       9.44472e+06            148      2.37917e+06       80188  0     0   \n",
       "2       7.89673e+06            123           636502      141000  0     0   \n",
       "3       6.33327e+06            110           126078       55123  0     0   \n",
       "4       4.74614e+06             73           284973       33204  0     0   \n",
       "\n",
       "   MPUA  UA  \n",
       "0     0   1  \n",
       "1     0   1  \n",
       "2     1   0  \n",
       "3     1   0  \n",
       "4     1   0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "wRur1PIuZEbu"
   },
   "outputs": [],
   "source": [
    "df_cat_1_1 = df_cat_1.drop(columns = ['City','State','Popuation [2001]','Sex Ratio','Median Age','Avg Temp','Water Purity','H Index','Covid Cases'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 402
    },
    "colab_type": "code",
    "id": "1QFaMwdBZEbz",
    "outputId": "67b444dd-262d-4a0a-efa6-d8301c2f699b"
   },
   "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>Population [2011]</th>\n",
       "      <th>SWM</th>\n",
       "      <th>Toilets Avl</th>\n",
       "      <th>Female Population</th>\n",
       "      <th># of hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "      <th>M</th>\n",
       "      <th>M.Cl</th>\n",
       "      <th>MPUA</th>\n",
       "      <th>UA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.24424e+07</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>219</td>\n",
       "      <td>1.09244e+07</td>\n",
       "      <td>159</td>\n",
       "      <td>4.40892e+06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.10078e+07</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>215</td>\n",
       "      <td>9.44472e+06</td>\n",
       "      <td>148</td>\n",
       "      <td>2.37917e+06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.43668e+06</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>212</td>\n",
       "      <td>7.89673e+06</td>\n",
       "      <td>123</td>\n",
       "      <td>636502</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6.80997e+06</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>217</td>\n",
       "      <td>6.33327e+06</td>\n",
       "      <td>110</td>\n",
       "      <td>126078</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.57058e+06</td>\n",
       "      <td>LOW</td>\n",
       "      <td>227</td>\n",
       "      <td>4.74614e+06</td>\n",
       "      <td>73</td>\n",
       "      <td>284973</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>36954</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>68</td>\n",
       "      <td>31263</td>\n",
       "      <td>19</td>\n",
       "      <td>284973</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>779</th>\n",
       "      <td>36947</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>62</td>\n",
       "      <td>34915</td>\n",
       "      <td>22</td>\n",
       "      <td>1.4895e+06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>780</th>\n",
       "      <td>36828</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>98</td>\n",
       "      <td>37528</td>\n",
       "      <td>27</td>\n",
       "      <td>106153</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>781</th>\n",
       "      <td>36805</td>\n",
       "      <td>MEDIUM</td>\n",
       "      <td>63</td>\n",
       "      <td>33125</td>\n",
       "      <td>15</td>\n",
       "      <td>24720</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\n",
       "      <td>36776</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>51</td>\n",
       "      <td>32694</td>\n",
       "      <td>30</td>\n",
       "      <td>3.10406e+06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>783 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Population [2011]     SWM Toilets Avl Female Population # of hospitals  \\\n",
       "0         1.24424e+07  MEDIUM         219       1.09244e+07            159   \n",
       "1         1.10078e+07  MEDIUM         215       9.44472e+06            148   \n",
       "2         8.43668e+06    HIGH         212       7.89673e+06            123   \n",
       "3         6.80997e+06  MEDIUM         217       6.33327e+06            110   \n",
       "4         5.57058e+06     LOW         227       4.74614e+06             73   \n",
       "..                ...     ...         ...               ...            ...   \n",
       "778             36954  MEDIUM          68             31263             19   \n",
       "779             36947  MEDIUM          62             34915             22   \n",
       "780             36828    HIGH          98             37528             27   \n",
       "781             36805  MEDIUM          63             33125             15   \n",
       "782             36776    HIGH          51             32694             30   \n",
       "\n",
       "    Foreign Visitors  M  M.Cl  MPUA  UA  \n",
       "0        4.40892e+06  0     0     0   1  \n",
       "1        2.37917e+06  0     0     0   1  \n",
       "2             636502  0     0     1   0  \n",
       "3             126078  0     0     1   0  \n",
       "4             284973  0     0     1   0  \n",
       "..               ... ..   ...   ...  ..  \n",
       "778           284973  1     0     0   0  \n",
       "779       1.4895e+06  1     0     0   0  \n",
       "780           106153  1     0     0   0  \n",
       "781            24720  0     0     0   1  \n",
       "782      3.10406e+06  0     0     0   1  \n",
       "\n",
       "[783 rows x 10 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat_1_1.head(785)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "2CkPY8biZEb3"
   },
   "outputs": [],
   "source": [
    "dumm=pd.get_dummies(df_cat_1_1[\"SWM\"])\n",
    "df_cat_1_1=df_cat_1_1.drop('SWM',axis=1)\n",
    "df_cat_1_1=pd.concat([df_cat_1_1,dumm],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 399,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "JrOAafr7ZEb5"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 402
    },
    "colab_type": "code",
    "id": "zR8ph__JZEb9",
    "outputId": "13c590ff-cb5d-4e5e-8fb6-d1aa24576bd0"
   },
   "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>Population [2011]</th>\n",
       "      <th>Toilets Avl</th>\n",
       "      <th>Female Population</th>\n",
       "      <th># of hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "      <th>M</th>\n",
       "      <th>M.Cl</th>\n",
       "      <th>MPUA</th>\n",
       "      <th>UA</th>\n",
       "      <th>HIGH</th>\n",
       "      <th>LOW</th>\n",
       "      <th>MEDIUM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.24424e+07</td>\n",
       "      <td>219</td>\n",
       "      <td>1.09244e+07</td>\n",
       "      <td>159</td>\n",
       "      <td>4.40892e+06</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.10078e+07</td>\n",
       "      <td>215</td>\n",
       "      <td>9.44472e+06</td>\n",
       "      <td>148</td>\n",
       "      <td>2.37917e+06</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.43668e+06</td>\n",
       "      <td>212</td>\n",
       "      <td>7.89673e+06</td>\n",
       "      <td>123</td>\n",
       "      <td>636502</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>3</th>\n",
       "      <td>6.80997e+06</td>\n",
       "      <td>217</td>\n",
       "      <td>6.33327e+06</td>\n",
       "      <td>110</td>\n",
       "      <td>126078</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>4</th>\n",
       "      <td>5.57058e+06</td>\n",
       "      <td>227</td>\n",
       "      <td>4.74614e+06</td>\n",
       "      <td>73</td>\n",
       "      <td>284973</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>36954</td>\n",
       "      <td>68</td>\n",
       "      <td>31263</td>\n",
       "      <td>19</td>\n",
       "      <td>284973</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>779</th>\n",
       "      <td>36947</td>\n",
       "      <td>62</td>\n",
       "      <td>34915</td>\n",
       "      <td>22</td>\n",
       "      <td>1.4895e+06</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>780</th>\n",
       "      <td>36828</td>\n",
       "      <td>98</td>\n",
       "      <td>37528</td>\n",
       "      <td>27</td>\n",
       "      <td>106153</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>781</th>\n",
       "      <td>36805</td>\n",
       "      <td>63</td>\n",
       "      <td>33125</td>\n",
       "      <td>15</td>\n",
       "      <td>24720</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\n",
       "      <td>36776</td>\n",
       "      <td>51</td>\n",
       "      <td>32694</td>\n",
       "      <td>30</td>\n",
       "      <td>3.10406e+06</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>783 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Population [2011] Toilets Avl Female Population # of hospitals  \\\n",
       "0         1.24424e+07         219       1.09244e+07            159   \n",
       "1         1.10078e+07         215       9.44472e+06            148   \n",
       "2         8.43668e+06         212       7.89673e+06            123   \n",
       "3         6.80997e+06         217       6.33327e+06            110   \n",
       "4         5.57058e+06         227       4.74614e+06             73   \n",
       "..                ...         ...               ...            ...   \n",
       "778             36954          68             31263             19   \n",
       "779             36947          62             34915             22   \n",
       "780             36828          98             37528             27   \n",
       "781             36805          63             33125             15   \n",
       "782             36776          51             32694             30   \n",
       "\n",
       "    Foreign Visitors  M  M.Cl  MPUA  UA  HIGH  LOW  MEDIUM  \n",
       "0        4.40892e+06  0     0     0   1     0    0       1  \n",
       "1        2.37917e+06  0     0     0   1     0    0       1  \n",
       "2             636502  0     0     1   0     1    0       0  \n",
       "3             126078  0     0     1   0     0    0       1  \n",
       "4             284973  0     0     1   0     0    1       0  \n",
       "..               ... ..   ...   ...  ..   ...  ...     ...  \n",
       "778           284973  1     0     0   0     0    0       1  \n",
       "779       1.4895e+06  1     0     0   0     0    0       1  \n",
       "780           106153  1     0     0   0     1    0       0  \n",
       "781            24720  0     0     0   1     0    0       1  \n",
       "782      3.10406e+06  0     0     0   1     1    0       0  \n",
       "\n",
       "[783 rows x 12 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat_1_1.head(783)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "AIOj0wXxZEb_"
   },
   "outputs": [],
   "source": [
    "df_cat_1_1 = df_cat_1_1.drop(columns = ['Population [2011]','Toilets Avl','Female Population','# of hospitals','Foreign Visitors'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 402
    },
    "colab_type": "code",
    "id": "2H307jDEZEcC",
    "outputId": "6fab9218-26b0-4e36-8e4c-d14ebdcf8453"
   },
   "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>M</th>\n",
       "      <th>M.Cl</th>\n",
       "      <th>MPUA</th>\n",
       "      <th>UA</th>\n",
       "      <th>HIGH</th>\n",
       "      <th>LOW</th>\n",
       "      <th>MEDIUM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>3</th>\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>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>779</th>\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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>780</th>\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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>781</th>\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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>783 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     M  M.Cl  MPUA  UA  HIGH  LOW  MEDIUM\n",
       "0    0     0     0   1     0    0       1\n",
       "1    0     0     0   1     0    0       1\n",
       "2    0     0     1   0     1    0       0\n",
       "3    0     0     1   0     0    0       1\n",
       "4    0     0     1   0     0    1       0\n",
       "..  ..   ...   ...  ..   ...  ...     ...\n",
       "778  1     0     0   0     0    0       1\n",
       "779  1     0     0   0     0    0       1\n",
       "780  1     0     0   0     1    0       0\n",
       "781  0     0     0   1     0    0       1\n",
       "782  0     0     0   1     1    0       0\n",
       "\n",
       "[783 rows x 7 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat_1_1.head(784)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "zxCxl7gyZEcE"
   },
   "outputs": [],
   "source": [
    "df_cat_2 = pd.concat([Fn_df,df_cat_1_1],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 195
    },
    "colab_type": "code",
    "id": "YEhS8bEbZEcI",
    "outputId": "f42045b8-3344-43ba-8220-66f36d32d1a9"
   },
   "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>Population_2011</th>\n",
       "      <th>Toilets</th>\n",
       "      <th>Female Pop</th>\n",
       "      <th>Hospitals</th>\n",
       "      <th>Foreign Visitors</th>\n",
       "      <th>M</th>\n",
       "      <th>M.Cl</th>\n",
       "      <th>MPUA</th>\n",
       "      <th>UA</th>\n",
       "      <th>HIGH</th>\n",
       "      <th>LOW</th>\n",
       "      <th>MEDIUM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12442373.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>10924403.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>4408916.0</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11007835.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>9444722.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>2379169.0</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8436675.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>7896728.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>636502.0</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>3</th>\n",
       "      <td>6809970.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>6333272.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>126078.0</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>4</th>\n",
       "      <td>5570585.0</td>\n",
       "      <td>227.0</td>\n",
       "      <td>4746138.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>284973.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Population_2011  Toilets  Female Pop  Hospitals  Foreign Visitors  M  M.Cl  \\\n",
       "0       12442373.0    219.0  10924403.0      159.0         4408916.0  0     0   \n",
       "1       11007835.0    215.0   9444722.0      148.0         2379169.0  0     0   \n",
       "2        8436675.0    212.0   7896728.0      123.0          636502.0  0     0   \n",
       "3        6809970.0    217.0   6333272.0      110.0          126078.0  0     0   \n",
       "4        5570585.0    227.0   4746138.0       73.0          284973.0  0     0   \n",
       "\n",
       "   MPUA  UA  HIGH  LOW  MEDIUM  \n",
       "0     0   1     0    0       1  \n",
       "1     0   1     0    0       1  \n",
       "2     1   0     1    0       0  \n",
       "3     1   0     0    0       1  \n",
       "4     1   0     0    1       0  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat_2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scaling & Train-Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "JULuY-f6ZEcL"
   },
   "outputs": [],
   "source": [
    "X = df_cat_2.iloc[:,[0,1,3,4,]].values\n",
    "y = df_cat_1.iloc[:,14].values.astype(np.float64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 235
    },
    "colab_type": "code",
    "id": "Bh5faWrJZEcN",
    "outputId": "2fd2faad-dde3-4dc4-a48e-ea5df245622c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.2442373e+07, 2.1900000e+02, 1.5900000e+02, 4.4089160e+06],\n",
       "       [1.1007835e+07, 2.1500000e+02, 1.4800000e+02, 2.3791690e+06],\n",
       "       [8.4366750e+06, 2.1200000e+02, 1.2300000e+02, 6.3650200e+05],\n",
       "       ...,\n",
       "       [3.6828000e+04, 9.8000000e+01, 2.7000000e+01, 1.0615300e+05],\n",
       "       [3.6805000e+04, 6.3000000e+01, 1.5000000e+01, 2.4720000e+04],\n",
       "       [3.6776000e+04, 5.1000000e+01, 3.0000000e+01, 3.1040600e+06]])"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "wlZQLypVZEcQ"
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "jWKiPV0FZEcT"
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.1,random_state=101)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "lXUnvzhoZEcW"
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "0swiAt4iZEcb"
   },
   "outputs": [],
   "source": [
    "scaler = MinMaxScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "2SvVfoMQZEce"
   },
   "outputs": [],
   "source": [
    "X_train= scaler.fit_transform(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "oK-YznRGZEcg"
   },
   "outputs": [],
   "source": [
    "X_test = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "4jf-BfYvZEck",
    "outputId": "03a64093-44c8-4b4b-a91a-cfed3fdbde1e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(704, 4)"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "NpkfMGCrZEcq",
    "outputId": "1aa80ef2-818a-48ad-fcbd-4e6453a434c1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(79, 4)"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "XZ2krG8JcDwD",
    "outputId": "14e7bd50-cef7-465f-9e65-bce5b8f95bc2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  9980.   2409.   9083.   2460.  10652.  10488.  11103.   9850.   6391.\n",
      "   2052.   8051.   2193.   2808.  10608.   2428.   2398.  10218.   1652.\n",
      "   2674.   2654.   2160.   2119.  11254.   2576.   2158.   2538.   8263.\n",
      "  20018.   9141.   4038.   2052.   2481.   7521.  10720.   9205.   2816.\n",
      "   2910.  10933.   2006.   2029.   1103.   2447.   2784.   9779.   2916.\n",
      "   2382.   2430.   2351.   2625.   2258.   2648.   2240.   2275.   2143.\n",
      "   2320.   2278.   2506.   8344.   3702.   2029.   2474.   2335.  10485.\n",
      "   4316.   4937.  15003.   8363.   2677.   2473.   2307.   2520.   9179.\n",
      "   2797.   8797.   2464.   4967.   8997.   3506.   2279.   1387.   2148.\n",
      "   2069.   2374.   7172.   2220.  15764.   2579.   1997.   2105. 141000.\n",
      "   2722.   2238.   2739.   2385.   4459.   7906.   2477.   2360.  10082.\n",
      "    449.   9502.   2198.   2450.   2291.   2313.   2582.   2523.   2805.\n",
      "  10071.   2123.   7812.   2571.   3076.   2184.  10287.  20839. 145606.\n",
      "   2576.   2281.  12365.   2596.   2285.   9439.   4424.   2630.  33204.\n",
      "    525.  22861.   2602.   2013.   8440.    759.    428.   9309.   2306.\n",
      "   2223.   2584.   6147.   9971.   2481.   9985.   2532.   2242.   2074.\n",
      "   8701.   2189.   2081.   2677.   2343.   2820.   2774.  10557.  12265.\n",
      "   2874.   2318.   1985.   2587.  13590.   2744.  24402.   2548.  11045.\n",
      "  10774.  10197.   3877.   2220.   2351.   2355.   7067.  10251.   2081.\n",
      "   2601.   9809.   1277.   8162.   9571.   9995.   2536.   2016.   2551.\n",
      "   5261.   9958.  10283.   3807.   2305.   3004.   9923.   9221.   4066.\n",
      "  11114.   9840.   1285.   9372.   8171.   2301.   2790.   2478.   2610.\n",
      "   1902.   2211.  10585.   2716.  10239.   2270.   8484.   9537.   2228.\n",
      "   5255.   2040.   2487.  10036.   2260.   1450.   7308.   2605.   8881.\n",
      "   2273.   1531.   2103.   2983.   2713.   8800. 163115.   8134.   2353.\n",
      "   5683.  12486.    579.  11243.   9829.   6245.    677.   1988.   2828.\n",
      "   2372.  10586.   2208.   2628.   2027.   2121.   2523.   2995.  10283.\n",
      "  10673.   2465.   9486.   2622.   1937.   2895.   2323.   2372.   2247.\n",
      "   2096.   2797.  10219.    334.   2188.   2203.   2268.   2425.   2052.\n",
      "   9131.   2590.   4738.   2871.   2158.   3023.   5514.   2220.   8811.\n",
      "   2384.   1974.   2877.   9602.   2515.   2265.    891.   2351.   2538.\n",
      "   8584.   2380.   9343.   2114.   2285.   9538.   2323.   2213.  10261.\n",
      "   4697.   9572.   2895.   2353.   2232.   2512.   2490.   4205.  20133.\n",
      "   2240.   2355.   8891.   2327.   2445.   1222.   2208.   2962.   2339.\n",
      "   5498.  21374.   2642.   2535.   2537.   8536.   1946.   2887.   9846.\n",
      "   2363.  27416.   2268.  10186.   2523.   2548.   2387.   8842.   2535.\n",
      "   9538.   2628.  10193.  14249.   9711.   4236.  12294.  15118.  10406.\n",
      "   2913.   2694.  10383.   2587.   7089.   2671.   2067.   2081.   2270.\n",
      "   2247.   9064.   2674.   2369.   2347.   2581.   2892.   4023.   2430.\n",
      "   3201.  10024.  19525.   2374.   5132.  10233.   9883.   2027.   2431.\n",
      "   2315.   1692.   2352.   2232.   9632.   2286.   2490.   2089.   9561.\n",
      "   3630.   2258.   9096.   2441.   7681.   2663.  10380.   8747.  10003.\n",
      " 150793.   2184.   2374.   2132.   2585.   1121.   2599.   2445.   9705.\n",
      "   8517.  23610.   8134.   2187.  11537.   9441.   2265.   2995.  12446.\n",
      "   3014.   1996.   2523.   2490.  14001.   2378.   2486.   2506.   2068.\n",
      "   9361.   2561.   2274.  10070.   2338.    947.   2254.   2434.   2564.\n",
      "   2273.   8910.   2460.   8795.  15764.   2259.   2293.   2163.   4025.\n",
      "   2355.  10272.   2431.   8771.    877.   9465.   9151.   3315.   2554.\n",
      "   2467.   9430.   2683.   2390.   2172.   1958.   2582.   2383.  10280.\n",
      "   2439.   2805.   7729.   2600.  10627.   2436.   2130.   2562.   2132.\n",
      "   4816.   2323.   8300.   2741.   3598.   2648.   9441.   6092.   2053.\n",
      "    887.  12847.   9061.   2686.   2689.   2506.   2178.   2901.   2001.\n",
      "   2270.   2403.  11510.  12234.   2315.   2045.   2184.   8107.   8677.\n",
      "   1591.   2076.   2479.  11137.   4764.   2280.   8843.   2320.   8459.\n",
      "   9403.   9049.  10250.  24507.   2185.   2288.   2054.  80188.   2402.\n",
      "   2252.   2248.  19818.   2123.   2306.  44700.   2534.   1944.   9792.\n",
      "   2568.   5595.   2819.    900.   2265.   2262.   2098.   2478.   1945.\n",
      "   1845.   2116.   2741.   2697.   8786.   2200.   2016.  50341.    528.\n",
      "   2210.   2392.   2534.   2004.   9634.   8139.   2310.   2330.   9191.\n",
      "   2543.   2213.   6250.   2196.   2155.   2526.   2576.   3798.   8751.\n",
      "   8776.   2430.   2359.   2382.   6235.   2029.   2487.   2095.   2375.\n",
      "  13751.  34227.   2225.   2172.  10687.   2976.   5054.   2252.   2458.\n",
      "   2442.    595.   2390.   2061.   8843.   8300.   2208.   2210.  10128.\n",
      "   2175.  10608.   6031.   2796.   2257.   2089.   2660.   2205.  30609.\n",
      "   9171.   3148.   2649.   2197.   2301.  10418.   1978.   8901.   8852.\n",
      "   2208.   2747.   3834.   2389.   3811.   2568.   1634.   2364.   2379.\n",
      "  25127.   2607.   2495.   5368.    571.   2449.   9174.   1043.   9179.\n",
      "   2386.   9991.  10140.   8005.   2322.   5989.   2706.   9775.   2250.\n",
      "  10476.   2220.  55123.   2314.   2175.   4066.   2478.    779.   2490.\n",
      "   7697.   2287.   2411.   2810.   2225.   2555.  21674.   9881.  10895.\n",
      "   2892.   2216.   2086.   8419.   3007.   2576.  22413.   2523.   2523.\n",
      "   2750.   2403.   2137.   1985.   2012.   2514.  10126.  10317.   4172.\n",
      "   3017.   2584.   2295.   8244.   2520.   2676.   2886.   2663.   2069.\n",
      "   2276.   8263.   2353.   2230.   2031.   2165.   9991.   9398.   2180.\n",
      "   2605.  10608.   8911.   1983.   3092.   7682.   2567.   2582.   2808.\n",
      "   3317.   2568.   8699.   2473.   2345.   2213.   8911.   1775.   4303.\n",
      "   2283.   2308.   8540.  21005.   2073. 145606.   8797.   2490.   2064.\n",
      "  10476.   2199.   2851.   2188.   2767.   1919.   9052.   2215.   2161.\n",
      "   2091.   2448.]\n"
     ]
    }
   ],
   "source": [
    "print(y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "kPtQ5W4lCnvh"
   },
   "source": [
    "# Creating Multi-Layer Perceptron Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "EskKMjhdZEct"
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, Activation\n",
    "from tensorflow.keras.optimizers import Adam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "1L9Py6sHcEMd"
   },
   "outputs": [],
   "source": [
    "from tensorflow.keras.callbacks import EarlyStopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 319
    },
    "colab_type": "code",
    "id": "qs6owvGV8dqM",
    "outputId": "f79858dc-7a5a-40e1-f013-82152d6325bf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_4\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_20 (Dense)             (None, 128)               640       \n",
      "_________________________________________________________________\n",
      "dense_21 (Dense)             (None, 256)               33024     \n",
      "_________________________________________________________________\n",
      "dense_22 (Dense)             (None, 256)               65792     \n",
      "_________________________________________________________________\n",
      "dense_23 (Dense)             (None, 256)               65792     \n",
      "_________________________________________________________________\n",
      "dense_24 (Dense)             (None, 1)                 257       \n",
      "=================================================================\n",
      "Total params: 165,505\n",
      "Trainable params: 165,505\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "NN_model = Sequential()\n",
    "\n",
    "# The Input Layer :\n",
    "NN_model.add(Dense(128, kernel_initializer='normal',input_dim = X_train.shape[1], activation='relu'))\n",
    "\n",
    "# The Hidden Layers :\n",
    "NN_model.add(Dense(256, kernel_initializer='normal',activation='relu'))\n",
    "NN_model.add(Dense(256, kernel_initializer='normal',activation='relu'))\n",
    "NN_model.add(Dense(256, kernel_initializer='normal',activation='relu'))\n",
    "\n",
    "# The Output Layer :\n",
    "NN_model.add(Dense(1, kernel_initializer='normal',activation='linear'))\n",
    "\n",
    "# Compile the network :\n",
    "NN_model.compile(loss='mean_absolute_error', optimizer='adam', metrics=[tf.keras.metrics.RootMeanSquaredError()])\n",
    "NN_model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 558
    },
    "colab_type": "code",
    "id": "sf4dom3j8r4F",
    "outputId": "4cd6d018-fc00-4be5-d570-352ba81926f8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/2000\n",
      "10/10 [==============================] - 0s 10ms/step - loss: 6331.3066 - root_mean_squared_error: 14565.2188 - val_loss: 6544.4331 - val_root_mean_squared_error: 18320.0469\n",
      "Epoch 2/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 6329.4287 - root_mean_squared_error: 14564.1387 - val_loss: 6539.7168 - val_root_mean_squared_error: 18317.6816\n",
      "Epoch 3/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 6316.9165 - root_mean_squared_error: 14556.9971 - val_loss: 6512.5195 - val_root_mean_squared_error: 18303.9219\n",
      "Epoch 4/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 6256.4370 - root_mean_squared_error: 14526.6367 - val_loss: 6397.1338 - val_root_mean_squared_error: 18245.8281\n",
      "Epoch 5/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 6029.8813 - root_mean_squared_error: 14394.6074 - val_loss: 6005.9155 - val_root_mean_squared_error: 18053.2754\n",
      "Epoch 6/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 5358.3315 - root_mean_squared_error: 14003.7881 - val_loss: 4895.3662 - val_root_mean_squared_error: 17546.2383\n",
      "Epoch 7/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 4143.4556 - root_mean_squared_error: 13273.1992 - val_loss: 4161.7271 - val_root_mean_squared_error: 16699.9746\n",
      "Epoch 8/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 3921.3196 - root_mean_squared_error: 12612.1641 - val_loss: 4204.9546 - val_root_mean_squared_error: 16542.2539\n",
      "Epoch 9/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 3749.1265 - root_mean_squared_error: 12698.3232 - val_loss: 3935.8469 - val_root_mean_squared_error: 16795.1523\n",
      "Epoch 10/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 3669.8179 - root_mean_squared_error: 12787.5762 - val_loss: 3885.1250 - val_root_mean_squared_error: 16703.8809\n",
      "Epoch 11/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 3594.4736 - root_mean_squared_error: 12612.3574 - val_loss: 3849.4719 - val_root_mean_squared_error: 16540.2891\n",
      "Epoch 12/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 3523.1406 - root_mean_squared_error: 12501.2822 - val_loss: 3762.3289 - val_root_mean_squared_error: 16515.1758\n",
      "Epoch 13/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 3444.0479 - root_mean_squared_error: 12445.6016 - val_loss: 3683.5256 - val_root_mean_squared_error: 16446.0566\n",
      "Epoch 14/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 3361.6560 - root_mean_squared_error: 12335.0986 - val_loss: 3600.0154 - val_root_mean_squared_error: 16285.8320\n",
      "Epoch 15/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 3265.0347 - root_mean_squared_error: 12121.6162 - val_loss: 3487.1428 - val_root_mean_squared_error: 16129.1953\n",
      "Epoch 16/2000\n",
      "10/10 [==============================] - 0s 17ms/step - loss: 3154.2429 - root_mean_squared_error: 11964.7324 - val_loss: 3346.0837 - val_root_mean_squared_error: 15996.5254\n",
      "Epoch 17/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 3052.5364 - root_mean_squared_error: 11783.7109 - val_loss: 3247.1597 - val_root_mean_squared_error: 15825.9600\n",
      "Epoch 18/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2991.9004 - root_mean_squared_error: 11692.9951 - val_loss: 3174.9258 - val_root_mean_squared_error: 15712.7549\n",
      "Epoch 19/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2954.1074 - root_mean_squared_error: 11505.6680 - val_loss: 3140.7041 - val_root_mean_squared_error: 15655.4521\n",
      "Epoch 20/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2940.6445 - root_mean_squared_error: 11487.5107 - val_loss: 3129.4153 - val_root_mean_squared_error: 15607.4453\n",
      "Epoch 21/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2926.0369 - root_mean_squared_error: 11398.6660 - val_loss: 3131.7131 - val_root_mean_squared_error: 15564.0586\n",
      "Epoch 22/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2915.8601 - root_mean_squared_error: 11405.5264 - val_loss: 3128.4231 - val_root_mean_squared_error: 15606.1807\n",
      "Epoch 23/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2910.5969 - root_mean_squared_error: 11347.7627 - val_loss: 3116.5171 - val_root_mean_squared_error: 15507.2266\n",
      "Epoch 24/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2895.9619 - root_mean_squared_error: 11348.1504 - val_loss: 3106.8728 - val_root_mean_squared_error: 15523.9453\n",
      "Epoch 25/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2882.8782 - root_mean_squared_error: 11265.4424 - val_loss: 3095.9905 - val_root_mean_squared_error: 15483.0176\n",
      "Epoch 26/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2869.1331 - root_mean_squared_error: 11249.8350 - val_loss: 3087.7603 - val_root_mean_squared_error: 15438.3867\n",
      "Epoch 27/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2855.8218 - root_mean_squared_error: 11180.1377 - val_loss: 3073.5837 - val_root_mean_squared_error: 15447.4434\n",
      "Epoch 28/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2852.5344 - root_mean_squared_error: 11182.1680 - val_loss: 3063.5747 - val_root_mean_squared_error: 15416.7939\n",
      "Epoch 29/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2833.9663 - root_mean_squared_error: 11145.6582 - val_loss: 3054.7390 - val_root_mean_squared_error: 15401.1709\n",
      "Epoch 30/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2826.7432 - root_mean_squared_error: 11114.6904 - val_loss: 3045.7927 - val_root_mean_squared_error: 15367.2793\n",
      "Epoch 31/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2812.3374 - root_mean_squared_error: 11061.8193 - val_loss: 3039.7634 - val_root_mean_squared_error: 15330.4756\n",
      "Epoch 32/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2815.3870 - root_mean_squared_error: 11076.5430 - val_loss: 3041.7734 - val_root_mean_squared_error: 15272.9551\n",
      "Epoch 33/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2817.8611 - root_mean_squared_error: 10995.8477 - val_loss: 3025.9434 - val_root_mean_squared_error: 15322.8145\n",
      "Epoch 34/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2806.9932 - root_mean_squared_error: 10891.8643 - val_loss: 3012.0854 - val_root_mean_squared_error: 15169.1387\n",
      "Epoch 35/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2793.6030 - root_mean_squared_error: 10970.3340 - val_loss: 2999.2883 - val_root_mean_squared_error: 15180.8818\n",
      "Epoch 36/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2785.1348 - root_mean_squared_error: 10836.7715 - val_loss: 2991.1384 - val_root_mean_squared_error: 15157.7617\n",
      "Epoch 37/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2754.7959 - root_mean_squared_error: 10777.5742 - val_loss: 2995.0415 - val_root_mean_squared_error: 15032.5820\n",
      "Epoch 38/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2754.2969 - root_mean_squared_error: 10778.0986 - val_loss: 2970.5098 - val_root_mean_squared_error: 15056.2969\n",
      "Epoch 39/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2738.7554 - root_mean_squared_error: 10660.1445 - val_loss: 2955.1799 - val_root_mean_squared_error: 15031.0469\n",
      "Epoch 40/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2712.8196 - root_mean_squared_error: 10635.3760 - val_loss: 2966.6812 - val_root_mean_squared_error: 14887.6025\n",
      "Epoch 41/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2702.7815 - root_mean_squared_error: 10502.2852 - val_loss: 2932.1353 - val_root_mean_squared_error: 14886.8564\n",
      "Epoch 42/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2686.6694 - root_mean_squared_error: 10547.6934 - val_loss: 2923.3103 - val_root_mean_squared_error: 14838.6992\n",
      "Epoch 43/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2669.8701 - root_mean_squared_error: 10413.6953 - val_loss: 2913.7844 - val_root_mean_squared_error: 14776.1758\n",
      "Epoch 44/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2652.3704 - root_mean_squared_error: 10409.0928 - val_loss: 2897.6626 - val_root_mean_squared_error: 14764.5596\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 45/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2633.1353 - root_mean_squared_error: 10337.6172 - val_loss: 2899.5220 - val_root_mean_squared_error: 14622.9121\n",
      "Epoch 46/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2630.3723 - root_mean_squared_error: 10208.7910 - val_loss: 2867.3225 - val_root_mean_squared_error: 14609.6104\n",
      "Epoch 47/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2616.3003 - root_mean_squared_error: 10263.1357 - val_loss: 2865.8560 - val_root_mean_squared_error: 14545.9668\n",
      "Epoch 48/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2592.9387 - root_mean_squared_error: 10119.6182 - val_loss: 2852.8113 - val_root_mean_squared_error: 14468.5283\n",
      "Epoch 49/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2578.7576 - root_mean_squared_error: 10089.4180 - val_loss: 2826.1028 - val_root_mean_squared_error: 14378.3789\n",
      "Epoch 50/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2557.9158 - root_mean_squared_error: 9944.0400 - val_loss: 2818.7876 - val_root_mean_squared_error: 14276.1221\n",
      "Epoch 51/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2544.9727 - root_mean_squared_error: 9905.6748 - val_loss: 2808.1409 - val_root_mean_squared_error: 14220.2266\n",
      "Epoch 52/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2527.1523 - root_mean_squared_error: 9834.5879 - val_loss: 2787.7209 - val_root_mean_squared_error: 14191.3965\n",
      "Epoch 53/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2525.6008 - root_mean_squared_error: 9772.8643 - val_loss: 2774.9150 - val_root_mean_squared_error: 14111.6797\n",
      "Epoch 54/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2505.5615 - root_mean_squared_error: 9679.0889 - val_loss: 2792.3052 - val_root_mean_squared_error: 13918.4463\n",
      "Epoch 55/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2489.5161 - root_mean_squared_error: 9612.1377 - val_loss: 2747.8047 - val_root_mean_squared_error: 13972.2500\n",
      "Epoch 56/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2471.1130 - root_mean_squared_error: 9547.2236 - val_loss: 2735.1958 - val_root_mean_squared_error: 13819.2090\n",
      "Epoch 57/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2456.9492 - root_mean_squared_error: 9453.7090 - val_loss: 2715.7903 - val_root_mean_squared_error: 13791.5908\n",
      "Epoch 58/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2448.1614 - root_mean_squared_error: 9391.9971 - val_loss: 2709.3696 - val_root_mean_squared_error: 13699.5166\n",
      "Epoch 59/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2439.6023 - root_mean_squared_error: 9279.6777 - val_loss: 2700.3416 - val_root_mean_squared_error: 13527.1816\n",
      "Epoch 60/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2433.5342 - root_mean_squared_error: 9214.2725 - val_loss: 2736.6365 - val_root_mean_squared_error: 13417.0039\n",
      "Epoch 61/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2414.4546 - root_mean_squared_error: 9095.5322 - val_loss: 2685.3169 - val_root_mean_squared_error: 13375.8398\n",
      "Epoch 62/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2399.0085 - root_mean_squared_error: 9026.1660 - val_loss: 2690.5103 - val_root_mean_squared_error: 13280.5986\n",
      "Epoch 63/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2386.2383 - root_mean_squared_error: 8918.8662 - val_loss: 2692.1990 - val_root_mean_squared_error: 13063.6309\n",
      "Epoch 64/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2382.0505 - root_mean_squared_error: 8829.2500 - val_loss: 2713.8721 - val_root_mean_squared_error: 12954.1416\n",
      "Epoch 65/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2378.0698 - root_mean_squared_error: 8852.8691 - val_loss: 2702.5586 - val_root_mean_squared_error: 13006.1514\n",
      "Epoch 66/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2370.6128 - root_mean_squared_error: 8769.0205 - val_loss: 2675.1538 - val_root_mean_squared_error: 12952.2500\n",
      "Epoch 67/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2359.5215 - root_mean_squared_error: 8750.6807 - val_loss: 2662.1953 - val_root_mean_squared_error: 12978.4648\n",
      "Epoch 68/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2357.0862 - root_mean_squared_error: 8736.0186 - val_loss: 2655.8865 - val_root_mean_squared_error: 12939.4463\n",
      "Epoch 69/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2355.3254 - root_mean_squared_error: 8768.0430 - val_loss: 2680.7698 - val_root_mean_squared_error: 12922.2891\n",
      "Epoch 70/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2356.0876 - root_mean_squared_error: 8729.1602 - val_loss: 2667.8201 - val_root_mean_squared_error: 12855.4941\n",
      "Epoch 71/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2347.0183 - root_mean_squared_error: 8715.9385 - val_loss: 2679.2410 - val_root_mean_squared_error: 12860.8545\n",
      "Epoch 72/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2357.5793 - root_mean_squared_error: 8696.4980 - val_loss: 2662.1611 - val_root_mean_squared_error: 12919.3311\n",
      "Epoch 73/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2348.5085 - root_mean_squared_error: 8686.3350 - val_loss: 2675.6775 - val_root_mean_squared_error: 12798.6377\n",
      "Epoch 74/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2343.7095 - root_mean_squared_error: 8695.8643 - val_loss: 2659.7407 - val_root_mean_squared_error: 12936.0566\n",
      "Epoch 75/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2345.7412 - root_mean_squared_error: 8734.3467 - val_loss: 2680.7158 - val_root_mean_squared_error: 12900.6885\n",
      "Epoch 76/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2341.4592 - root_mean_squared_error: 8695.4756 - val_loss: 2659.0278 - val_root_mean_squared_error: 12822.8857\n",
      "Epoch 77/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2345.7366 - root_mean_squared_error: 8707.1035 - val_loss: 2688.4788 - val_root_mean_squared_error: 12818.0127\n",
      "Epoch 78/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2359.8748 - root_mean_squared_error: 8661.2021 - val_loss: 2658.2830 - val_root_mean_squared_error: 12888.5498\n",
      "Epoch 79/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2358.0327 - root_mean_squared_error: 8652.7373 - val_loss: 2673.9294 - val_root_mean_squared_error: 12907.6465\n",
      "Epoch 80/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2364.5947 - root_mean_squared_error: 8789.0996 - val_loss: 2758.9980 - val_root_mean_squared_error: 12828.8496\n",
      "Epoch 81/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2368.3630 - root_mean_squared_error: 8696.4121 - val_loss: 2674.3462 - val_root_mean_squared_error: 12982.7871\n",
      "Epoch 82/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2358.0212 - root_mean_squared_error: 8771.1445 - val_loss: 2697.7275 - val_root_mean_squared_error: 12773.0957\n",
      "Epoch 83/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2348.7568 - root_mean_squared_error: 8664.1279 - val_loss: 2680.7397 - val_root_mean_squared_error: 12997.7002\n",
      "Epoch 84/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2370.9255 - root_mean_squared_error: 8734.4043 - val_loss: 2685.8870 - val_root_mean_squared_error: 12882.2891\n",
      "Epoch 85/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2356.6836 - root_mean_squared_error: 8816.8623 - val_loss: 2676.4609 - val_root_mean_squared_error: 12897.9824\n",
      "Epoch 86/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2380.9482 - root_mean_squared_error: 8704.3252 - val_loss: 2683.8123 - val_root_mean_squared_error: 13103.5244\n",
      "Epoch 87/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2370.1367 - root_mean_squared_error: 8796.7627 - val_loss: 2732.6038 - val_root_mean_squared_error: 12857.9492\n",
      "Epoch 88/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2348.5737 - root_mean_squared_error: 8743.4902 - val_loss: 2660.3279 - val_root_mean_squared_error: 12979.5312\n",
      "Epoch 89/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10/10 [==============================] - 0s 6ms/step - loss: 2346.0479 - root_mean_squared_error: 8738.7793 - val_loss: 2656.0044 - val_root_mean_squared_error: 12929.0928\n",
      "Epoch 90/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2341.9895 - root_mean_squared_error: 8785.8652 - val_loss: 2681.5627 - val_root_mean_squared_error: 12861.6973\n",
      "Epoch 91/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2331.9492 - root_mean_squared_error: 8753.0430 - val_loss: 2654.0581 - val_root_mean_squared_error: 12939.3438\n",
      "Epoch 92/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2334.6924 - root_mean_squared_error: 8717.5449 - val_loss: 2665.3340 - val_root_mean_squared_error: 12917.0742\n",
      "Epoch 93/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2336.4912 - root_mean_squared_error: 8755.8037 - val_loss: 2673.3826 - val_root_mean_squared_error: 12853.3184\n",
      "Epoch 94/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2327.3413 - root_mean_squared_error: 8715.1318 - val_loss: 2654.2031 - val_root_mean_squared_error: 12953.4668\n",
      "Epoch 95/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2335.6042 - root_mean_squared_error: 8723.0576 - val_loss: 2679.3342 - val_root_mean_squared_error: 12820.4346\n",
      "Epoch 96/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2328.0942 - root_mean_squared_error: 8715.4033 - val_loss: 2668.6506 - val_root_mean_squared_error: 12942.3418\n",
      "Epoch 97/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2336.8328 - root_mean_squared_error: 8765.7773 - val_loss: 2669.9341 - val_root_mean_squared_error: 12923.1797\n",
      "Epoch 98/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2337.0176 - root_mean_squared_error: 8707.6533 - val_loss: 2662.7144 - val_root_mean_squared_error: 12882.4238\n",
      "Epoch 99/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2327.8435 - root_mean_squared_error: 8710.8867 - val_loss: 2679.2776 - val_root_mean_squared_error: 12837.0830\n",
      "Epoch 100/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2329.2332 - root_mean_squared_error: 8717.6494 - val_loss: 2673.1211 - val_root_mean_squared_error: 12863.6592\n",
      "Epoch 101/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2343.2815 - root_mean_squared_error: 8655.9756 - val_loss: 2669.2913 - val_root_mean_squared_error: 12843.4434\n",
      "Epoch 102/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2339.3005 - root_mean_squared_error: 8712.1592 - val_loss: 2681.5029 - val_root_mean_squared_error: 12858.4756\n",
      "Epoch 103/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2335.4023 - root_mean_squared_error: 8723.4082 - val_loss: 2670.4319 - val_root_mean_squared_error: 12946.8809\n",
      "Epoch 104/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2343.1038 - root_mean_squared_error: 8707.3564 - val_loss: 2681.1919 - val_root_mean_squared_error: 12811.8828\n",
      "Epoch 105/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2329.5381 - root_mean_squared_error: 8725.3984 - val_loss: 2674.6951 - val_root_mean_squared_error: 12872.0693\n",
      "Epoch 106/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2337.2610 - root_mean_squared_error: 8741.1221 - val_loss: 2673.6284 - val_root_mean_squared_error: 12859.9648\n",
      "Epoch 107/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2326.0962 - root_mean_squared_error: 8712.2686 - val_loss: 2683.5205 - val_root_mean_squared_error: 12838.8984\n",
      "Epoch 108/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2330.8970 - root_mean_squared_error: 8688.6191 - val_loss: 2671.7861 - val_root_mean_squared_error: 12835.9648\n",
      "Epoch 109/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2328.3862 - root_mean_squared_error: 8659.5049 - val_loss: 2673.9736 - val_root_mean_squared_error: 12847.2529\n",
      "Epoch 110/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2331.9529 - root_mean_squared_error: 8726.4033 - val_loss: 2674.6489 - val_root_mean_squared_error: 12901.8096\n",
      "Epoch 111/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2333.3381 - root_mean_squared_error: 8722.6289 - val_loss: 2684.2366 - val_root_mean_squared_error: 12801.5166\n",
      "Epoch 112/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2331.6177 - root_mean_squared_error: 8700.3145 - val_loss: 2684.7981 - val_root_mean_squared_error: 12805.7559\n",
      "Epoch 113/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2333.9565 - root_mean_squared_error: 8728.4639 - val_loss: 2679.0930 - val_root_mean_squared_error: 12915.8711\n",
      "Epoch 114/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2329.8105 - root_mean_squared_error: 8689.1963 - val_loss: 2677.6345 - val_root_mean_squared_error: 12796.6768\n",
      "Epoch 115/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2335.2183 - root_mean_squared_error: 8663.9492 - val_loss: 2714.9004 - val_root_mean_squared_error: 12679.8623\n",
      "Epoch 116/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2354.5874 - root_mean_squared_error: 8658.8652 - val_loss: 2682.3816 - val_root_mean_squared_error: 12919.2656\n",
      "Epoch 117/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2334.4746 - root_mean_squared_error: 8680.0762 - val_loss: 2679.3438 - val_root_mean_squared_error: 12915.7705\n",
      "Epoch 118/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2330.5139 - root_mean_squared_error: 8757.0645 - val_loss: 2695.4866 - val_root_mean_squared_error: 12854.8340\n",
      "Epoch 119/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2331.4812 - root_mean_squared_error: 8690.6553 - val_loss: 2668.7302 - val_root_mean_squared_error: 12910.8193\n",
      "Epoch 120/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2343.1667 - root_mean_squared_error: 8745.6650 - val_loss: 2688.5134 - val_root_mean_squared_error: 12831.8750\n",
      "Epoch 121/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2339.3555 - root_mean_squared_error: 8846.1006 - val_loss: 2677.2981 - val_root_mean_squared_error: 12975.4844\n",
      "Epoch 122/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2337.6860 - root_mean_squared_error: 8725.2139 - val_loss: 2677.5581 - val_root_mean_squared_error: 12999.2969\n",
      "Epoch 123/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2343.2578 - root_mean_squared_error: 8717.7773 - val_loss: 2686.0974 - val_root_mean_squared_error: 12855.3955\n",
      "Epoch 124/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.2039 - root_mean_squared_error: 8700.7861 - val_loss: 2672.3926 - val_root_mean_squared_error: 12905.4541\n",
      "Epoch 125/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2337.5803 - root_mean_squared_error: 8752.4922 - val_loss: 2682.9438 - val_root_mean_squared_error: 12891.2812\n",
      "Epoch 126/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2323.7830 - root_mean_squared_error: 8709.8057 - val_loss: 2673.6270 - val_root_mean_squared_error: 12850.2725\n",
      "Epoch 127/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2327.7031 - root_mean_squared_error: 8700.6689 - val_loss: 2672.3333 - val_root_mean_squared_error: 12893.2178\n",
      "Epoch 128/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2323.8105 - root_mean_squared_error: 8744.8584 - val_loss: 2680.1858 - val_root_mean_squared_error: 12900.1660\n",
      "Epoch 129/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2319.9126 - root_mean_squared_error: 8709.0967 - val_loss: 2683.4089 - val_root_mean_squared_error: 12868.9717\n",
      "Epoch 130/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2326.1611 - root_mean_squared_error: 8719.7617 - val_loss: 2696.1196 - val_root_mean_squared_error: 12829.2949\n",
      "Epoch 131/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2326.1746 - root_mean_squared_error: 8691.6875 - val_loss: 2670.2622 - val_root_mean_squared_error: 12919.5254\n",
      "Epoch 132/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.2527 - root_mean_squared_error: 8739.1592 - val_loss: 2677.5994 - val_root_mean_squared_error: 12878.1777\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 133/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.5068 - root_mean_squared_error: 8686.1133 - val_loss: 2683.4141 - val_root_mean_squared_error: 12841.4570\n",
      "Epoch 134/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2328.0188 - root_mean_squared_error: 8669.5615 - val_loss: 2681.4846 - val_root_mean_squared_error: 12784.8525\n",
      "Epoch 135/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2319.0405 - root_mean_squared_error: 8708.1299 - val_loss: 2678.0359 - val_root_mean_squared_error: 12926.6924\n",
      "Epoch 136/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2325.2185 - root_mean_squared_error: 8748.7402 - val_loss: 2679.7986 - val_root_mean_squared_error: 12908.5840\n",
      "Epoch 137/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2321.6738 - root_mean_squared_error: 8722.4492 - val_loss: 2675.1182 - val_root_mean_squared_error: 12895.5264\n",
      "Epoch 138/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2321.7388 - root_mean_squared_error: 8705.9648 - val_loss: 2676.8677 - val_root_mean_squared_error: 12888.9033\n",
      "Epoch 139/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2334.5972 - root_mean_squared_error: 8776.9033 - val_loss: 2695.6938 - val_root_mean_squared_error: 12873.4336\n",
      "Epoch 140/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2328.0312 - root_mean_squared_error: 8750.6680 - val_loss: 2669.2622 - val_root_mean_squared_error: 12948.1924\n",
      "Epoch 141/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2320.9165 - root_mean_squared_error: 8700.4092 - val_loss: 2683.2805 - val_root_mean_squared_error: 12859.5303\n",
      "Epoch 142/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2318.8403 - root_mean_squared_error: 8703.6689 - val_loss: 2676.2190 - val_root_mean_squared_error: 12889.7568\n",
      "Epoch 143/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2320.0190 - root_mean_squared_error: 8716.3584 - val_loss: 2684.5583 - val_root_mean_squared_error: 12857.9766\n",
      "Epoch 144/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2325.8542 - root_mean_squared_error: 8655.9678 - val_loss: 2678.6389 - val_root_mean_squared_error: 12848.0518\n",
      "Epoch 145/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2330.7686 - root_mean_squared_error: 8716.4395 - val_loss: 2693.9314 - val_root_mean_squared_error: 12832.2207\n",
      "Epoch 146/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2336.3936 - root_mean_squared_error: 8719.4844 - val_loss: 2672.3264 - val_root_mean_squared_error: 12950.6885\n",
      "Epoch 147/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.6079 - root_mean_squared_error: 8700.7324 - val_loss: 2697.4631 - val_root_mean_squared_error: 12781.0273\n",
      "Epoch 148/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2330.0925 - root_mean_squared_error: 8659.4805 - val_loss: 2679.1052 - val_root_mean_squared_error: 12854.4766\n",
      "Epoch 149/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2322.0605 - root_mean_squared_error: 8682.0430 - val_loss: 2673.2246 - val_root_mean_squared_error: 12870.0840\n",
      "Epoch 150/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2323.1389 - root_mean_squared_error: 8646.7529 - val_loss: 2671.1318 - val_root_mean_squared_error: 12780.6289\n",
      "Epoch 151/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.1216 - root_mean_squared_error: 8628.5439 - val_loss: 2685.0735 - val_root_mean_squared_error: 12745.6260\n",
      "Epoch 152/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2338.9731 - root_mean_squared_error: 8759.5859 - val_loss: 2689.3833 - val_root_mean_squared_error: 12907.4375\n",
      "Epoch 153/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2331.0557 - root_mean_squared_error: 8718.0723 - val_loss: 2674.3269 - val_root_mean_squared_error: 12938.0225\n",
      "Epoch 154/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.1729 - root_mean_squared_error: 8711.2383 - val_loss: 2671.3230 - val_root_mean_squared_error: 12855.4873\n",
      "Epoch 155/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2320.7390 - root_mean_squared_error: 8688.5146 - val_loss: 2677.9226 - val_root_mean_squared_error: 12883.7236\n",
      "Epoch 156/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2320.4807 - root_mean_squared_error: 8711.2998 - val_loss: 2681.7139 - val_root_mean_squared_error: 12825.3008\n",
      "Epoch 157/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2318.2822 - root_mean_squared_error: 8671.6260 - val_loss: 2682.4438 - val_root_mean_squared_error: 12791.9004\n",
      "Epoch 158/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2322.2295 - root_mean_squared_error: 8700.1514 - val_loss: 2681.1965 - val_root_mean_squared_error: 12855.8584\n",
      "Epoch 159/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2317.3877 - root_mean_squared_error: 8715.8838 - val_loss: 2683.6631 - val_root_mean_squared_error: 12855.1982\n",
      "Epoch 160/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2321.2078 - root_mean_squared_error: 8725.4785 - val_loss: 2687.5764 - val_root_mean_squared_error: 12818.8896\n",
      "Epoch 161/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2328.0962 - root_mean_squared_error: 8668.3174 - val_loss: 2670.8103 - val_root_mean_squared_error: 12856.3203\n",
      "Epoch 162/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2332.1533 - root_mean_squared_error: 8749.4277 - val_loss: 2700.4358 - val_root_mean_squared_error: 12801.7432\n",
      "Epoch 163/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2326.2959 - root_mean_squared_error: 8684.0850 - val_loss: 2665.3667 - val_root_mean_squared_error: 12913.1309\n",
      "Epoch 164/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2322.6721 - root_mean_squared_error: 8707.9092 - val_loss: 2694.4724 - val_root_mean_squared_error: 12829.5059\n",
      "Epoch 165/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2331.8235 - root_mean_squared_error: 8667.2539 - val_loss: 2674.4070 - val_root_mean_squared_error: 12959.4814\n",
      "Epoch 166/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.4573 - root_mean_squared_error: 8687.1523 - val_loss: 2674.9521 - val_root_mean_squared_error: 12816.3418\n",
      "Epoch 167/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2327.7217 - root_mean_squared_error: 8715.9326 - val_loss: 2677.4136 - val_root_mean_squared_error: 12869.5117\n",
      "Epoch 168/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2340.9324 - root_mean_squared_error: 8665.1250 - val_loss: 2682.3831 - val_root_mean_squared_error: 12979.7354\n",
      "Epoch 169/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2337.1082 - root_mean_squared_error: 8723.6035 - val_loss: 2695.1355 - val_root_mean_squared_error: 12846.3096\n",
      "Epoch 170/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2317.4001 - root_mean_squared_error: 8741.2861 - val_loss: 2672.1816 - val_root_mean_squared_error: 12966.3428\n",
      "Epoch 171/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2332.8792 - root_mean_squared_error: 8725.1738 - val_loss: 2681.9409 - val_root_mean_squared_error: 12773.8955\n",
      "Epoch 172/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2329.0894 - root_mean_squared_error: 8709.6025 - val_loss: 2685.8535 - val_root_mean_squared_error: 12819.1797\n",
      "Epoch 173/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2329.8633 - root_mean_squared_error: 8675.7441 - val_loss: 2674.6958 - val_root_mean_squared_error: 12955.8477\n",
      "Epoch 174/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2339.6162 - root_mean_squared_error: 8690.6748 - val_loss: 2674.1255 - val_root_mean_squared_error: 12825.1719\n",
      "Epoch 175/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2312.4299 - root_mean_squared_error: 8674.3359 - val_loss: 2670.5798 - val_root_mean_squared_error: 12868.2910\n",
      "Epoch 176/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2314.6738 - root_mean_squared_error: 8690.9150 - val_loss: 2680.1990 - val_root_mean_squared_error: 12861.1318\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 177/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2319.0181 - root_mean_squared_error: 8658.7734 - val_loss: 2677.8794 - val_root_mean_squared_error: 12843.8613\n",
      "Epoch 178/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.6802 - root_mean_squared_error: 8701.1641 - val_loss: 2682.9866 - val_root_mean_squared_error: 12794.9229\n",
      "Epoch 179/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2317.5232 - root_mean_squared_error: 8684.2402 - val_loss: 2673.5566 - val_root_mean_squared_error: 12821.3457\n",
      "Epoch 180/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2321.6042 - root_mean_squared_error: 8607.7861 - val_loss: 2672.9646 - val_root_mean_squared_error: 12856.2402\n",
      "Epoch 181/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2322.2188 - root_mean_squared_error: 8692.1758 - val_loss: 2690.1643 - val_root_mean_squared_error: 12842.1309\n",
      "Epoch 182/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2325.9834 - root_mean_squared_error: 8740.7539 - val_loss: 2675.4275 - val_root_mean_squared_error: 12863.3926\n",
      "Epoch 183/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2324.1313 - root_mean_squared_error: 8692.2373 - val_loss: 2675.6003 - val_root_mean_squared_error: 12862.1768\n",
      "Epoch 184/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2312.2859 - root_mean_squared_error: 8671.2998 - val_loss: 2677.3472 - val_root_mean_squared_error: 12849.5801\n",
      "Epoch 185/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2313.1201 - root_mean_squared_error: 8678.0684 - val_loss: 2670.9832 - val_root_mean_squared_error: 12874.1201\n",
      "Epoch 186/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2313.1865 - root_mean_squared_error: 8692.3877 - val_loss: 2677.1719 - val_root_mean_squared_error: 12817.6162\n",
      "Epoch 187/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2313.7278 - root_mean_squared_error: 8660.7383 - val_loss: 2677.1523 - val_root_mean_squared_error: 12832.6025\n",
      "Epoch 188/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2312.7690 - root_mean_squared_error: 8660.7656 - val_loss: 2675.2271 - val_root_mean_squared_error: 12862.2061\n",
      "Epoch 189/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2312.8486 - root_mean_squared_error: 8691.5723 - val_loss: 2681.0000 - val_root_mean_squared_error: 12848.1494\n",
      "Epoch 190/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2319.7400 - root_mean_squared_error: 8658.4717 - val_loss: 2669.6799 - val_root_mean_squared_error: 12884.0693\n",
      "Epoch 191/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2338.6567 - root_mean_squared_error: 8725.1738 - val_loss: 2699.8201 - val_root_mean_squared_error: 12800.0488\n",
      "Epoch 192/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2342.6030 - root_mean_squared_error: 8634.5547 - val_loss: 2668.4883 - val_root_mean_squared_error: 13013.4795\n",
      "Epoch 193/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2342.7395 - root_mean_squared_error: 8723.5186 - val_loss: 2680.1526 - val_root_mean_squared_error: 12822.1875\n",
      "Epoch 194/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2315.5015 - root_mean_squared_error: 8674.7949 - val_loss: 2669.0874 - val_root_mean_squared_error: 12904.1299\n",
      "Epoch 195/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2313.2554 - root_mean_squared_error: 8665.9521 - val_loss: 2673.7480 - val_root_mean_squared_error: 12814.5713\n",
      "Epoch 196/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2309.6458 - root_mean_squared_error: 8657.8428 - val_loss: 2675.1284 - val_root_mean_squared_error: 12809.7891\n",
      "Epoch 197/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2314.5879 - root_mean_squared_error: 8659.8428 - val_loss: 2676.7847 - val_root_mean_squared_error: 12873.8770\n",
      "Epoch 198/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2311.4653 - root_mean_squared_error: 8664.1924 - val_loss: 2673.7014 - val_root_mean_squared_error: 12798.2959\n",
      "Epoch 199/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2315.9768 - root_mean_squared_error: 8652.9033 - val_loss: 2672.8611 - val_root_mean_squared_error: 12764.6602\n",
      "Epoch 200/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2315.4626 - root_mean_squared_error: 8620.7568 - val_loss: 2676.7834 - val_root_mean_squared_error: 12843.9053\n",
      "Epoch 201/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2313.3445 - root_mean_squared_error: 8665.1113 - val_loss: 2676.5176 - val_root_mean_squared_error: 12855.9873\n",
      "Epoch 202/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2315.5640 - root_mean_squared_error: 8680.0137 - val_loss: 2668.0195 - val_root_mean_squared_error: 12908.7158\n",
      "Epoch 203/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2312.5269 - root_mean_squared_error: 8706.2812 - val_loss: 2686.8752 - val_root_mean_squared_error: 12837.0840\n",
      "Epoch 204/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2310.7063 - root_mean_squared_error: 8682.7588 - val_loss: 2666.6152 - val_root_mean_squared_error: 12924.7695\n",
      "Epoch 205/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2314.2126 - root_mean_squared_error: 8695.7656 - val_loss: 2679.6172 - val_root_mean_squared_error: 12800.4229\n",
      "Epoch 206/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2312.0828 - root_mean_squared_error: 8654.6318 - val_loss: 2666.2739 - val_root_mean_squared_error: 12931.6514\n",
      "Epoch 207/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2311.2021 - root_mean_squared_error: 8688.3477 - val_loss: 2678.4297 - val_root_mean_squared_error: 12825.0596\n",
      "Epoch 208/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2309.7881 - root_mean_squared_error: 8639.5449 - val_loss: 2671.7800 - val_root_mean_squared_error: 12852.0820\n",
      "Epoch 209/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2308.2759 - root_mean_squared_error: 8667.6152 - val_loss: 2669.5210 - val_root_mean_squared_error: 12775.6641\n",
      "Epoch 210/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2319.1279 - root_mean_squared_error: 8667.9736 - val_loss: 2673.6533 - val_root_mean_squared_error: 12831.9346\n",
      "Epoch 211/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2307.1680 - root_mean_squared_error: 8638.3867 - val_loss: 2673.4832 - val_root_mean_squared_error: 12824.3730\n",
      "Epoch 212/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2312.3044 - root_mean_squared_error: 8706.0068 - val_loss: 2678.1440 - val_root_mean_squared_error: 12874.4102\n",
      "Epoch 213/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2308.3857 - root_mean_squared_error: 8668.1455 - val_loss: 2666.4587 - val_root_mean_squared_error: 12863.2900\n",
      "Epoch 214/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2310.8745 - root_mean_squared_error: 8649.2266 - val_loss: 2675.5374 - val_root_mean_squared_error: 12811.4844\n",
      "Epoch 215/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2310.8352 - root_mean_squared_error: 8650.2988 - val_loss: 2672.4390 - val_root_mean_squared_error: 12845.7432\n",
      "Epoch 216/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2306.2583 - root_mean_squared_error: 8673.0957 - val_loss: 2671.7480 - val_root_mean_squared_error: 12862.8945\n",
      "Epoch 217/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2322.1738 - root_mean_squared_error: 8686.6309 - val_loss: 2679.0496 - val_root_mean_squared_error: 12734.0869\n",
      "Epoch 218/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2310.3088 - root_mean_squared_error: 8637.7578 - val_loss: 2672.4241 - val_root_mean_squared_error: 12802.7842\n",
      "Epoch 219/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2304.2549 - root_mean_squared_error: 8628.0967 - val_loss: 2663.5347 - val_root_mean_squared_error: 12873.3887\n",
      "Epoch 220/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2310.6721 - root_mean_squared_error: 8647.3184 - val_loss: 2674.3728 - val_root_mean_squared_error: 12808.4199\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 221/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2303.9580 - root_mean_squared_error: 8627.2725 - val_loss: 2666.2776 - val_root_mean_squared_error: 12826.6875\n",
      "Epoch 222/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2316.2266 - root_mean_squared_error: 8645.9033 - val_loss: 2674.6597 - val_root_mean_squared_error: 12789.7529\n",
      "Epoch 223/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2305.2773 - root_mean_squared_error: 8640.1436 - val_loss: 2668.6140 - val_root_mean_squared_error: 12877.3418\n",
      "Epoch 224/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2307.3672 - root_mean_squared_error: 8662.2500 - val_loss: 2674.6992 - val_root_mean_squared_error: 12821.8496\n",
      "Epoch 225/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2311.1843 - root_mean_squared_error: 8646.8984 - val_loss: 2667.7932 - val_root_mean_squared_error: 12755.3535\n",
      "Epoch 226/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2315.3477 - root_mean_squared_error: 8653.8818 - val_loss: 2675.1418 - val_root_mean_squared_error: 12796.8965\n",
      "Epoch 227/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2309.3584 - root_mean_squared_error: 8602.3604 - val_loss: 2665.0764 - val_root_mean_squared_error: 12804.1221\n",
      "Epoch 228/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2307.5996 - root_mean_squared_error: 8605.1602 - val_loss: 2674.7649 - val_root_mean_squared_error: 12791.5547\n",
      "Epoch 229/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2312.2212 - root_mean_squared_error: 8686.0215 - val_loss: 2671.8103 - val_root_mean_squared_error: 12881.5059\n",
      "Epoch 230/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2306.1821 - root_mean_squared_error: 8699.2031 - val_loss: 2672.2874 - val_root_mean_squared_error: 12837.0225\n",
      "Epoch 231/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2303.0981 - root_mean_squared_error: 8638.1865 - val_loss: 2668.3650 - val_root_mean_squared_error: 12782.5107\n",
      "Epoch 232/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2311.5908 - root_mean_squared_error: 8577.3760 - val_loss: 2670.1538 - val_root_mean_squared_error: 12812.0430\n",
      "Epoch 233/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2308.9741 - root_mean_squared_error: 8647.3203 - val_loss: 2674.0906 - val_root_mean_squared_error: 12778.0908\n",
      "Epoch 234/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2307.8533 - root_mean_squared_error: 8608.9951 - val_loss: 2666.9092 - val_root_mean_squared_error: 12908.6084\n",
      "Epoch 235/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2332.2705 - root_mean_squared_error: 8683.8936 - val_loss: 2675.9705 - val_root_mean_squared_error: 12757.7256\n",
      "Epoch 236/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2304.0796 - root_mean_squared_error: 8611.1553 - val_loss: 2668.5000 - val_root_mean_squared_error: 12837.0176\n",
      "Epoch 237/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2304.5630 - root_mean_squared_error: 8643.2119 - val_loss: 2671.5361 - val_root_mean_squared_error: 12792.6201\n",
      "Epoch 238/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2303.9885 - root_mean_squared_error: 8629.0439 - val_loss: 2660.4163 - val_root_mean_squared_error: 12795.4473\n",
      "Epoch 239/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2308.7114 - root_mean_squared_error: 8614.5078 - val_loss: 2667.0542 - val_root_mean_squared_error: 12834.8223\n",
      "Epoch 240/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2304.1716 - root_mean_squared_error: 8662.8945 - val_loss: 2673.9854 - val_root_mean_squared_error: 12791.8672\n",
      "Epoch 241/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2316.6626 - root_mean_squared_error: 8660.7500 - val_loss: 2654.1091 - val_root_mean_squared_error: 12805.3223\n",
      "Epoch 242/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2316.2266 - root_mean_squared_error: 8566.9746 - val_loss: 2664.7563 - val_root_mean_squared_error: 12721.5127\n",
      "Epoch 243/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2318.2012 - root_mean_squared_error: 8599.6934 - val_loss: 2697.6621 - val_root_mean_squared_error: 12715.5361\n",
      "Epoch 244/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2308.7385 - root_mean_squared_error: 8603.9902 - val_loss: 2661.7588 - val_root_mean_squared_error: 12890.9062\n",
      "Epoch 245/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2308.8921 - root_mean_squared_error: 8645.9346 - val_loss: 2687.3364 - val_root_mean_squared_error: 12688.3418\n",
      "Epoch 246/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2325.4583 - root_mean_squared_error: 8689.8838 - val_loss: 2649.8281 - val_root_mean_squared_error: 12838.6465\n",
      "Epoch 247/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2304.2979 - root_mean_squared_error: 8592.7012 - val_loss: 2655.0569 - val_root_mean_squared_error: 12799.6836\n",
      "Epoch 248/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2296.6658 - root_mean_squared_error: 8601.9873 - val_loss: 2663.8320 - val_root_mean_squared_error: 12768.7070\n",
      "Epoch 249/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2298.4102 - root_mean_squared_error: 8614.3965 - val_loss: 2672.9736 - val_root_mean_squared_error: 12736.3672\n",
      "Epoch 250/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2298.5486 - root_mean_squared_error: 8561.3457 - val_loss: 2661.3225 - val_root_mean_squared_error: 12802.0508\n",
      "Epoch 251/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2301.2988 - root_mean_squared_error: 8605.5049 - val_loss: 2675.4707 - val_root_mean_squared_error: 12728.0312\n",
      "Epoch 252/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2305.9424 - root_mean_squared_error: 8590.5439 - val_loss: 2657.5803 - val_root_mean_squared_error: 12838.6064\n",
      "Epoch 253/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2297.7502 - root_mean_squared_error: 8588.0127 - val_loss: 2673.1299 - val_root_mean_squared_error: 12708.7148\n",
      "Epoch 254/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2306.4146 - root_mean_squared_error: 8576.2852 - val_loss: 2657.9956 - val_root_mean_squared_error: 12779.1182\n",
      "Epoch 255/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2299.9285 - root_mean_squared_error: 8538.6221 - val_loss: 2654.0225 - val_root_mean_squared_error: 12732.4932\n",
      "Epoch 256/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2304.8613 - root_mean_squared_error: 8638.1064 - val_loss: 2670.4373 - val_root_mean_squared_error: 12751.8926\n",
      "Epoch 257/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2297.8306 - root_mean_squared_error: 8582.6309 - val_loss: 2664.2747 - val_root_mean_squared_error: 12761.7695\n",
      "Epoch 258/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2295.5190 - root_mean_squared_error: 8566.6816 - val_loss: 2657.6150 - val_root_mean_squared_error: 12783.7588\n",
      "Epoch 259/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2296.4866 - root_mean_squared_error: 8606.7871 - val_loss: 2664.2009 - val_root_mean_squared_error: 12773.3936\n",
      "Epoch 260/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2292.0996 - root_mean_squared_error: 8599.3672 - val_loss: 2652.3152 - val_root_mean_squared_error: 12814.2178\n",
      "Epoch 261/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2295.5488 - root_mean_squared_error: 8576.3633 - val_loss: 2658.2078 - val_root_mean_squared_error: 12704.9316\n",
      "Epoch 262/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2294.7195 - root_mean_squared_error: 8542.2998 - val_loss: 2660.8086 - val_root_mean_squared_error: 12841.4375\n",
      "Epoch 263/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2309.1047 - root_mean_squared_error: 8650.8135 - val_loss: 2652.3286 - val_root_mean_squared_error: 12769.5010\n",
      "Epoch 264/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2300.6323 - root_mean_squared_error: 8615.4844 - val_loss: 2642.8179 - val_root_mean_squared_error: 12787.4248\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 265/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2297.7988 - root_mean_squared_error: 8580.6025 - val_loss: 2648.3994 - val_root_mean_squared_error: 12825.7988\n",
      "Epoch 266/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2293.5659 - root_mean_squared_error: 8622.8545 - val_loss: 2659.8401 - val_root_mean_squared_error: 12707.0049\n",
      "Epoch 267/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2300.2485 - root_mean_squared_error: 8595.5176 - val_loss: 2648.6277 - val_root_mean_squared_error: 12863.9824\n",
      "Epoch 268/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2298.7742 - root_mean_squared_error: 8571.0566 - val_loss: 2661.1133 - val_root_mean_squared_error: 12742.2734\n",
      "Epoch 269/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2294.4788 - root_mean_squared_error: 8585.0947 - val_loss: 2654.5574 - val_root_mean_squared_error: 12857.8252\n",
      "Epoch 270/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2289.5518 - root_mean_squared_error: 8568.9600 - val_loss: 2652.1479 - val_root_mean_squared_error: 12740.7148\n",
      "Epoch 271/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2298.5352 - root_mean_squared_error: 8591.6582 - val_loss: 2646.0183 - val_root_mean_squared_error: 12705.4668\n",
      "Epoch 272/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2314.1233 - root_mean_squared_error: 8485.0615 - val_loss: 2651.2073 - val_root_mean_squared_error: 12746.8896\n",
      "Epoch 273/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2312.2610 - root_mean_squared_error: 8600.6562 - val_loss: 2671.6785 - val_root_mean_squared_error: 12621.3213\n",
      "Epoch 274/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2293.4858 - root_mean_squared_error: 8546.3584 - val_loss: 2645.0703 - val_root_mean_squared_error: 12788.6572\n",
      "Epoch 275/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2284.7217 - root_mean_squared_error: 8549.1963 - val_loss: 2655.8516 - val_root_mean_squared_error: 12664.7070\n",
      "Epoch 276/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2292.3049 - root_mean_squared_error: 8566.3369 - val_loss: 2658.1147 - val_root_mean_squared_error: 12646.0703\n",
      "Epoch 277/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2288.1155 - root_mean_squared_error: 8516.3516 - val_loss: 2648.6763 - val_root_mean_squared_error: 12732.7422\n",
      "Epoch 278/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2287.3269 - root_mean_squared_error: 8566.7266 - val_loss: 2655.5249 - val_root_mean_squared_error: 12747.5068\n",
      "Epoch 279/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2284.7825 - root_mean_squared_error: 8560.8447 - val_loss: 2654.5557 - val_root_mean_squared_error: 12663.0459\n",
      "Epoch 280/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2283.8179 - root_mean_squared_error: 8513.7637 - val_loss: 2650.3398 - val_root_mean_squared_error: 12716.9990\n",
      "Epoch 281/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2284.4912 - root_mean_squared_error: 8566.7910 - val_loss: 2661.6021 - val_root_mean_squared_error: 12708.9980\n",
      "Epoch 282/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2288.8601 - root_mean_squared_error: 8551.5244 - val_loss: 2643.6868 - val_root_mean_squared_error: 12788.8662\n",
      "Epoch 283/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2294.6533 - root_mean_squared_error: 8535.1650 - val_loss: 2644.8560 - val_root_mean_squared_error: 12741.8418\n",
      "Epoch 284/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2282.5388 - root_mean_squared_error: 8565.4004 - val_loss: 2653.6833 - val_root_mean_squared_error: 12727.4268\n",
      "Epoch 285/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2283.7822 - root_mean_squared_error: 8523.4414 - val_loss: 2649.6104 - val_root_mean_squared_error: 12769.0684\n",
      "Epoch 286/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2282.2795 - root_mean_squared_error: 8555.8066 - val_loss: 2657.3677 - val_root_mean_squared_error: 12663.5439\n",
      "Epoch 287/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2304.0291 - root_mean_squared_error: 8560.3213 - val_loss: 2642.2214 - val_root_mean_squared_error: 12811.7393\n",
      "Epoch 288/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2284.7854 - root_mean_squared_error: 8573.5059 - val_loss: 2655.1353 - val_root_mean_squared_error: 12637.2529\n",
      "Epoch 289/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2285.5535 - root_mean_squared_error: 8536.6826 - val_loss: 2648.3203 - val_root_mean_squared_error: 12772.6328\n",
      "Epoch 290/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2282.6667 - root_mean_squared_error: 8568.4658 - val_loss: 2650.5442 - val_root_mean_squared_error: 12751.4814\n",
      "Epoch 291/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2282.4180 - root_mean_squared_error: 8512.4521 - val_loss: 2646.1152 - val_root_mean_squared_error: 12659.3525\n",
      "Epoch 292/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2282.3926 - root_mean_squared_error: 8488.4609 - val_loss: 2644.8994 - val_root_mean_squared_error: 12675.5439\n",
      "Epoch 293/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2284.6941 - root_mean_squared_error: 8564.4375 - val_loss: 2657.4341 - val_root_mean_squared_error: 12724.3115\n",
      "Epoch 294/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2288.5269 - root_mean_squared_error: 8524.7139 - val_loss: 2644.0098 - val_root_mean_squared_error: 12769.6514\n",
      "Epoch 295/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2283.1365 - root_mean_squared_error: 8569.6426 - val_loss: 2658.6396 - val_root_mean_squared_error: 12633.1152\n",
      "Epoch 296/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2293.2456 - root_mean_squared_error: 8475.5205 - val_loss: 2643.5237 - val_root_mean_squared_error: 12723.1035\n",
      "Epoch 297/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2287.2612 - root_mean_squared_error: 8496.2178 - val_loss: 2657.1707 - val_root_mean_squared_error: 12655.4512\n",
      "Epoch 298/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2289.8425 - root_mean_squared_error: 8556.1699 - val_loss: 2657.6423 - val_root_mean_squared_error: 12682.6787\n",
      "Epoch 299/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2282.8630 - root_mean_squared_error: 8476.9795 - val_loss: 2637.9675 - val_root_mean_squared_error: 12698.3164\n",
      "Epoch 300/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2274.8716 - root_mean_squared_error: 8510.9912 - val_loss: 2664.5151 - val_root_mean_squared_error: 12603.4023\n",
      "Epoch 301/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2290.0193 - root_mean_squared_error: 8533.6260 - val_loss: 2646.7046 - val_root_mean_squared_error: 12701.9912\n",
      "Epoch 302/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2275.2544 - root_mean_squared_error: 8511.2354 - val_loss: 2650.8911 - val_root_mean_squared_error: 12640.0176\n",
      "Epoch 303/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2277.9646 - root_mean_squared_error: 8493.4111 - val_loss: 2638.7378 - val_root_mean_squared_error: 12661.0713\n",
      "Epoch 304/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2276.4392 - root_mean_squared_error: 8467.3135 - val_loss: 2643.4775 - val_root_mean_squared_error: 12621.1406\n",
      "Epoch 305/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2275.3921 - root_mean_squared_error: 8477.8330 - val_loss: 2645.5750 - val_root_mean_squared_error: 12647.3545\n",
      "Epoch 306/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2275.4065 - root_mean_squared_error: 8491.0186 - val_loss: 2644.7900 - val_root_mean_squared_error: 12633.5498\n",
      "Epoch 307/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2274.7104 - root_mean_squared_error: 8503.6689 - val_loss: 2648.2573 - val_root_mean_squared_error: 12668.1523\n",
      "Epoch 308/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2278.1587 - root_mean_squared_error: 8523.7900 - val_loss: 2645.0188 - val_root_mean_squared_error: 12699.7803\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 309/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2270.6523 - root_mean_squared_error: 8478.3184 - val_loss: 2632.8823 - val_root_mean_squared_error: 12644.7051\n",
      "Epoch 310/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2277.7112 - root_mean_squared_error: 8467.5205 - val_loss: 2636.5962 - val_root_mean_squared_error: 12693.8105\n",
      "Epoch 311/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2280.3257 - root_mean_squared_error: 8484.4189 - val_loss: 2645.9668 - val_root_mean_squared_error: 12650.2783\n",
      "Epoch 312/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2275.0776 - root_mean_squared_error: 8519.5156 - val_loss: 2628.7834 - val_root_mean_squared_error: 12670.5332\n",
      "Epoch 313/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2268.9998 - root_mean_squared_error: 8495.7900 - val_loss: 2639.8169 - val_root_mean_squared_error: 12587.2783\n",
      "Epoch 314/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2281.8174 - root_mean_squared_error: 8443.1377 - val_loss: 2642.3491 - val_root_mean_squared_error: 12733.9297\n",
      "Epoch 315/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2281.8052 - root_mean_squared_error: 8516.5020 - val_loss: 2666.2163 - val_root_mean_squared_error: 12548.4385\n",
      "Epoch 316/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2292.1772 - root_mean_squared_error: 8491.8828 - val_loss: 2638.3906 - val_root_mean_squared_error: 12708.3887\n",
      "Epoch 317/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2272.3882 - root_mean_squared_error: 8436.9424 - val_loss: 2645.7363 - val_root_mean_squared_error: 12561.8789\n",
      "Epoch 318/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2274.7688 - root_mean_squared_error: 8484.7188 - val_loss: 2640.4868 - val_root_mean_squared_error: 12594.2910\n",
      "Epoch 319/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2279.7910 - root_mean_squared_error: 8397.7314 - val_loss: 2632.5432 - val_root_mean_squared_error: 12619.6562\n",
      "Epoch 320/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2269.4385 - root_mean_squared_error: 8450.7832 - val_loss: 2638.2529 - val_root_mean_squared_error: 12617.7969\n",
      "Epoch 321/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2264.1145 - root_mean_squared_error: 8449.2021 - val_loss: 2633.9631 - val_root_mean_squared_error: 12620.9385\n",
      "Epoch 322/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2267.2761 - root_mean_squared_error: 8443.0371 - val_loss: 2637.5149 - val_root_mean_squared_error: 12598.5352\n",
      "Epoch 323/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2275.6680 - root_mean_squared_error: 8451.1309 - val_loss: 2629.4622 - val_root_mean_squared_error: 12639.3301\n",
      "Epoch 324/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2264.5903 - root_mean_squared_error: 8410.5215 - val_loss: 2626.0950 - val_root_mean_squared_error: 12554.5225\n",
      "Epoch 325/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2285.5471 - root_mean_squared_error: 8502.2041 - val_loss: 2645.6433 - val_root_mean_squared_error: 12614.4004\n",
      "Epoch 326/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2275.1370 - root_mean_squared_error: 8446.0908 - val_loss: 2635.9172 - val_root_mean_squared_error: 12608.2959\n",
      "Epoch 327/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2265.1423 - root_mean_squared_error: 8401.2764 - val_loss: 2628.0142 - val_root_mean_squared_error: 12553.5059\n",
      "Epoch 328/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2264.1318 - root_mean_squared_error: 8412.8164 - val_loss: 2626.9639 - val_root_mean_squared_error: 12625.3975\n",
      "Epoch 329/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2268.8484 - root_mean_squared_error: 8426.4434 - val_loss: 2628.2896 - val_root_mean_squared_error: 12574.5029\n",
      "Epoch 330/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2263.4565 - root_mean_squared_error: 8407.8154 - val_loss: 2633.4500 - val_root_mean_squared_error: 12557.2324\n",
      "Epoch 331/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2258.6267 - root_mean_squared_error: 8416.8467 - val_loss: 2633.9475 - val_root_mean_squared_error: 12609.8936\n",
      "Epoch 332/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2261.6350 - root_mean_squared_error: 8406.4443 - val_loss: 2628.1594 - val_root_mean_squared_error: 12583.7236\n",
      "Epoch 333/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2262.8066 - root_mean_squared_error: 8443.8330 - val_loss: 2628.7976 - val_root_mean_squared_error: 12541.9717\n",
      "Epoch 334/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2257.2327 - root_mean_squared_error: 8392.1611 - val_loss: 2629.8364 - val_root_mean_squared_error: 12546.6895\n",
      "Epoch 335/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2254.9512 - root_mean_squared_error: 8383.4014 - val_loss: 2635.6509 - val_root_mean_squared_error: 12586.2822\n",
      "Epoch 336/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2258.5291 - root_mean_squared_error: 8413.9004 - val_loss: 2627.1948 - val_root_mean_squared_error: 12602.3379\n",
      "Epoch 337/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2260.6113 - root_mean_squared_error: 8365.7725 - val_loss: 2622.6089 - val_root_mean_squared_error: 12484.5381\n",
      "Epoch 338/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2261.5996 - root_mean_squared_error: 8353.2842 - val_loss: 2631.7639 - val_root_mean_squared_error: 12415.8516\n",
      "Epoch 339/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2261.6089 - root_mean_squared_error: 8368.0146 - val_loss: 2620.5659 - val_root_mean_squared_error: 12567.7891\n",
      "Epoch 340/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2268.6987 - root_mean_squared_error: 8314.5234 - val_loss: 2622.2168 - val_root_mean_squared_error: 12517.2012\n",
      "Epoch 341/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2263.4648 - root_mean_squared_error: 8439.2510 - val_loss: 2634.8752 - val_root_mean_squared_error: 12511.5674\n",
      "Epoch 342/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2257.2341 - root_mean_squared_error: 8378.5156 - val_loss: 2620.7222 - val_root_mean_squared_error: 12668.1064\n",
      "Epoch 343/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2257.5605 - root_mean_squared_error: 8438.6240 - val_loss: 2629.1733 - val_root_mean_squared_error: 12529.5908\n",
      "Epoch 344/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2254.8037 - root_mean_squared_error: 8356.9443 - val_loss: 2621.0642 - val_root_mean_squared_error: 12578.5420\n",
      "Epoch 345/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2260.6470 - root_mean_squared_error: 8405.8506 - val_loss: 2639.4141 - val_root_mean_squared_error: 12406.1328\n",
      "Epoch 346/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2254.8003 - root_mean_squared_error: 8302.4912 - val_loss: 2614.4832 - val_root_mean_squared_error: 12491.3926\n",
      "Epoch 347/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2254.8816 - root_mean_squared_error: 8354.8838 - val_loss: 2619.0945 - val_root_mean_squared_error: 12469.7588\n",
      "Epoch 348/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2250.4272 - root_mean_squared_error: 8371.6748 - val_loss: 2615.0552 - val_root_mean_squared_error: 12535.3242\n",
      "Epoch 349/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2252.9482 - root_mean_squared_error: 8341.8262 - val_loss: 2621.9480 - val_root_mean_squared_error: 12465.6826\n",
      "Epoch 350/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2243.9363 - root_mean_squared_error: 8325.6670 - val_loss: 2613.8728 - val_root_mean_squared_error: 12499.9326\n",
      "Epoch 351/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2250.8545 - root_mean_squared_error: 8387.5752 - val_loss: 2620.5525 - val_root_mean_squared_error: 12529.3564\n",
      "Epoch 352/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2252.4597 - root_mean_squared_error: 8329.9531 - val_loss: 2603.0591 - val_root_mean_squared_error: 12513.6748\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 353/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2248.3010 - root_mean_squared_error: 8313.1396 - val_loss: 2620.3635 - val_root_mean_squared_error: 12475.7119\n",
      "Epoch 354/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2247.8394 - root_mean_squared_error: 8301.8682 - val_loss: 2613.7437 - val_root_mean_squared_error: 12503.2510\n",
      "Epoch 355/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2247.9727 - root_mean_squared_error: 8331.7393 - val_loss: 2610.4788 - val_root_mean_squared_error: 12476.0049\n",
      "Epoch 356/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2242.8823 - root_mean_squared_error: 8358.1494 - val_loss: 2614.7297 - val_root_mean_squared_error: 12565.1484\n",
      "Epoch 357/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2245.0405 - root_mean_squared_error: 8363.1201 - val_loss: 2620.2664 - val_root_mean_squared_error: 12429.9629\n",
      "Epoch 358/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2247.6377 - root_mean_squared_error: 8326.0596 - val_loss: 2610.9622 - val_root_mean_squared_error: 12491.7334\n",
      "Epoch 359/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2240.7380 - root_mean_squared_error: 8317.9805 - val_loss: 2620.9966 - val_root_mean_squared_error: 12419.2988\n",
      "Epoch 360/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2250.2454 - root_mean_squared_error: 8295.0322 - val_loss: 2602.7935 - val_root_mean_squared_error: 12448.2793\n",
      "Epoch 361/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2256.3240 - root_mean_squared_error: 8226.5557 - val_loss: 2614.7222 - val_root_mean_squared_error: 12373.5986\n",
      "Epoch 362/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2242.9231 - root_mean_squared_error: 8332.9160 - val_loss: 2618.4932 - val_root_mean_squared_error: 12404.7070\n",
      "Epoch 363/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2248.7476 - root_mean_squared_error: 8261.7393 - val_loss: 2604.3196 - val_root_mean_squared_error: 12470.3008\n",
      "Epoch 364/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2246.0698 - root_mean_squared_error: 8250.4551 - val_loss: 2620.8618 - val_root_mean_squared_error: 12321.5762\n",
      "Epoch 365/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2244.5977 - root_mean_squared_error: 8301.7842 - val_loss: 2607.4548 - val_root_mean_squared_error: 12429.1904\n",
      "Epoch 366/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2245.5364 - root_mean_squared_error: 8220.8330 - val_loss: 2600.6853 - val_root_mean_squared_error: 12360.4102\n",
      "Epoch 367/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2239.0261 - root_mean_squared_error: 8235.9980 - val_loss: 2601.3589 - val_root_mean_squared_error: 12373.8633\n",
      "Epoch 368/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2232.5396 - root_mean_squared_error: 8254.2588 - val_loss: 2605.6055 - val_root_mean_squared_error: 12470.7129\n",
      "Epoch 369/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2239.2888 - root_mean_squared_error: 8294.5771 - val_loss: 2622.2563 - val_root_mean_squared_error: 12316.4346\n",
      "Epoch 370/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2235.8105 - root_mean_squared_error: 8266.2168 - val_loss: 2588.5654 - val_root_mean_squared_error: 12463.8691\n",
      "Epoch 371/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2236.6196 - root_mean_squared_error: 8243.7734 - val_loss: 2612.0269 - val_root_mean_squared_error: 12304.7275\n",
      "Epoch 372/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2231.4375 - root_mean_squared_error: 8221.1807 - val_loss: 2605.5637 - val_root_mean_squared_error: 12412.7607\n",
      "Epoch 373/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2227.1814 - root_mean_squared_error: 8259.3076 - val_loss: 2607.6570 - val_root_mean_squared_error: 12386.6934\n",
      "Epoch 374/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2229.2026 - root_mean_squared_error: 8291.5918 - val_loss: 2599.0483 - val_root_mean_squared_error: 12437.4395\n",
      "Epoch 375/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2222.6260 - root_mean_squared_error: 8265.0439 - val_loss: 2597.4534 - val_root_mean_squared_error: 12396.6611\n",
      "Epoch 376/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2225.8250 - root_mean_squared_error: 8253.9561 - val_loss: 2586.0708 - val_root_mean_squared_error: 12389.6064\n",
      "Epoch 377/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2222.8096 - root_mean_squared_error: 8238.8809 - val_loss: 2589.7776 - val_root_mean_squared_error: 12370.2832\n",
      "Epoch 378/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2225.8086 - root_mean_squared_error: 8234.8291 - val_loss: 2591.7798 - val_root_mean_squared_error: 12395.3721\n",
      "Epoch 379/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2223.9751 - root_mean_squared_error: 8208.1240 - val_loss: 2593.3740 - val_root_mean_squared_error: 12323.1670\n",
      "Epoch 380/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2219.4199 - root_mean_squared_error: 8207.2090 - val_loss: 2592.1604 - val_root_mean_squared_error: 12326.0332\n",
      "Epoch 381/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2221.0833 - root_mean_squared_error: 8243.1289 - val_loss: 2592.8154 - val_root_mean_squared_error: 12424.5918\n",
      "Epoch 382/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2220.8164 - root_mean_squared_error: 8218.2334 - val_loss: 2588.0034 - val_root_mean_squared_error: 12311.8506\n",
      "Epoch 383/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2223.1082 - root_mean_squared_error: 8238.6680 - val_loss: 2588.4897 - val_root_mean_squared_error: 12308.7119\n",
      "Epoch 384/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2212.8997 - root_mean_squared_error: 8204.2490 - val_loss: 2587.9172 - val_root_mean_squared_error: 12392.2852\n",
      "Epoch 385/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2218.1370 - root_mean_squared_error: 8215.0156 - val_loss: 2583.8113 - val_root_mean_squared_error: 12358.2695\n",
      "Epoch 386/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2210.6892 - root_mean_squared_error: 8197.6504 - val_loss: 2580.4092 - val_root_mean_squared_error: 12309.5322\n",
      "Epoch 387/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2213.1909 - root_mean_squared_error: 8149.7490 - val_loss: 2584.1162 - val_root_mean_squared_error: 12302.2744\n",
      "Epoch 388/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2224.3289 - root_mean_squared_error: 8252.0762 - val_loss: 2593.8921 - val_root_mean_squared_error: 12307.9834\n",
      "Epoch 389/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2214.8435 - root_mean_squared_error: 8173.1221 - val_loss: 2575.6189 - val_root_mean_squared_error: 12233.9287\n",
      "Epoch 390/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2210.8240 - root_mean_squared_error: 8130.9360 - val_loss: 2578.1262 - val_root_mean_squared_error: 12167.7354\n",
      "Epoch 391/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2214.7141 - root_mean_squared_error: 8159.8057 - val_loss: 2581.7205 - val_root_mean_squared_error: 12293.3936\n",
      "Epoch 392/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2213.5232 - root_mean_squared_error: 8153.8872 - val_loss: 2577.3267 - val_root_mean_squared_error: 12269.8994\n",
      "Epoch 393/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2202.3601 - root_mean_squared_error: 8157.2861 - val_loss: 2581.9497 - val_root_mean_squared_error: 12200.3193\n",
      "Epoch 394/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2204.6365 - root_mean_squared_error: 8093.4673 - val_loss: 2575.6238 - val_root_mean_squared_error: 12241.4072\n",
      "Epoch 395/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2204.1797 - root_mean_squared_error: 8170.8081 - val_loss: 2577.2263 - val_root_mean_squared_error: 12270.4775\n",
      "Epoch 396/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2207.2632 - root_mean_squared_error: 8161.7383 - val_loss: 2560.4878 - val_root_mean_squared_error: 12232.2754\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 397/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2211.8035 - root_mean_squared_error: 8096.0898 - val_loss: 2573.6318 - val_root_mean_squared_error: 12220.5791\n",
      "Epoch 398/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2207.3745 - root_mean_squared_error: 8160.3057 - val_loss: 2582.3726 - val_root_mean_squared_error: 12212.3594\n",
      "Epoch 399/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2203.9788 - root_mean_squared_error: 8100.2744 - val_loss: 2559.9961 - val_root_mean_squared_error: 12212.3574\n",
      "Epoch 400/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2210.8848 - root_mean_squared_error: 8121.9404 - val_loss: 2568.0220 - val_root_mean_squared_error: 12100.1367\n",
      "Epoch 401/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2203.7083 - root_mean_squared_error: 8111.3384 - val_loss: 2573.8469 - val_root_mean_squared_error: 12168.4648\n",
      "Epoch 402/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2202.5522 - root_mean_squared_error: 8082.9150 - val_loss: 2559.3774 - val_root_mean_squared_error: 12218.8311\n",
      "Epoch 403/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2197.8958 - root_mean_squared_error: 8090.0200 - val_loss: 2566.1013 - val_root_mean_squared_error: 12067.9668\n",
      "Epoch 404/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2192.5178 - root_mean_squared_error: 8021.2461 - val_loss: 2553.9653 - val_root_mean_squared_error: 12187.6865\n",
      "Epoch 405/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2201.3650 - root_mean_squared_error: 8016.8950 - val_loss: 2581.1492 - val_root_mean_squared_error: 11960.4893\n",
      "Epoch 406/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2191.0840 - root_mean_squared_error: 8044.1938 - val_loss: 2557.7402 - val_root_mean_squared_error: 12151.9277\n",
      "Epoch 407/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2186.9617 - root_mean_squared_error: 8063.4116 - val_loss: 2554.6206 - val_root_mean_squared_error: 12194.9404\n",
      "Epoch 408/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2184.1572 - root_mean_squared_error: 8080.2231 - val_loss: 2561.6887 - val_root_mean_squared_error: 12149.2178\n",
      "Epoch 409/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2182.1821 - root_mean_squared_error: 8014.2119 - val_loss: 2555.9006 - val_root_mean_squared_error: 12072.7646\n",
      "Epoch 410/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2183.3508 - root_mean_squared_error: 8027.1460 - val_loss: 2550.7234 - val_root_mean_squared_error: 12074.6748\n",
      "Epoch 411/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2177.3877 - root_mean_squared_error: 8030.8462 - val_loss: 2552.5288 - val_root_mean_squared_error: 12036.5439\n",
      "Epoch 412/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2209.7981 - root_mean_squared_error: 7932.9214 - val_loss: 2547.5293 - val_root_mean_squared_error: 11903.3594\n",
      "Epoch 413/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2196.7383 - root_mean_squared_error: 7980.2188 - val_loss: 2548.9658 - val_root_mean_squared_error: 11947.6191\n",
      "Epoch 414/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2191.1062 - root_mean_squared_error: 7983.1978 - val_loss: 2547.6189 - val_root_mean_squared_error: 11958.4531\n",
      "Epoch 415/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2172.4175 - root_mean_squared_error: 7978.6743 - val_loss: 2539.1250 - val_root_mean_squared_error: 12020.2793\n",
      "Epoch 416/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2173.0283 - root_mean_squared_error: 7971.6245 - val_loss: 2537.0276 - val_root_mean_squared_error: 11943.7910\n",
      "Epoch 417/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2184.0862 - root_mean_squared_error: 7995.1099 - val_loss: 2530.2776 - val_root_mean_squared_error: 11816.7139\n",
      "Epoch 418/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2176.4292 - root_mean_squared_error: 7965.1870 - val_loss: 2533.7529 - val_root_mean_squared_error: 11965.0234\n",
      "Epoch 419/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2167.3645 - root_mean_squared_error: 7900.0562 - val_loss: 2520.8313 - val_root_mean_squared_error: 11829.8848\n",
      "Epoch 420/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2166.2422 - root_mean_squared_error: 7901.6963 - val_loss: 2521.9099 - val_root_mean_squared_error: 11823.5127\n",
      "Epoch 421/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2164.9609 - root_mean_squared_error: 7883.0562 - val_loss: 2525.6465 - val_root_mean_squared_error: 11794.4473\n",
      "Epoch 422/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2160.5825 - root_mean_squared_error: 7885.3369 - val_loss: 2520.5320 - val_root_mean_squared_error: 11791.2402\n",
      "Epoch 423/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2163.5139 - root_mean_squared_error: 7893.7837 - val_loss: 2504.9438 - val_root_mean_squared_error: 11951.2822\n",
      "Epoch 424/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2176.6904 - root_mean_squared_error: 7928.6548 - val_loss: 2509.9709 - val_root_mean_squared_error: 11766.2197\n",
      "Epoch 425/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2165.6006 - root_mean_squared_error: 7956.8008 - val_loss: 2522.2351 - val_root_mean_squared_error: 11925.2617\n",
      "Epoch 426/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2198.2761 - root_mean_squared_error: 7900.2314 - val_loss: 2517.1272 - val_root_mean_squared_error: 11903.9766\n",
      "Epoch 427/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2160.6492 - root_mean_squared_error: 7871.7656 - val_loss: 2515.6365 - val_root_mean_squared_error: 11652.2676\n",
      "Epoch 428/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2150.8083 - root_mean_squared_error: 7849.8003 - val_loss: 2494.9299 - val_root_mean_squared_error: 11828.9600\n",
      "Epoch 429/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2149.5271 - root_mean_squared_error: 7843.5376 - val_loss: 2505.6990 - val_root_mean_squared_error: 11713.8418\n",
      "Epoch 430/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2142.5396 - root_mean_squared_error: 7809.0181 - val_loss: 2496.6289 - val_root_mean_squared_error: 11699.0654\n",
      "Epoch 431/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2142.6514 - root_mean_squared_error: 7858.9297 - val_loss: 2501.9143 - val_root_mean_squared_error: 11777.0361\n",
      "Epoch 432/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2151.2295 - root_mean_squared_error: 7828.3828 - val_loss: 2487.2202 - val_root_mean_squared_error: 11761.9424\n",
      "Epoch 433/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 2143.6472 - root_mean_squared_error: 7806.1187 - val_loss: 2511.5342 - val_root_mean_squared_error: 11517.7842\n",
      "Epoch 434/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2139.0427 - root_mean_squared_error: 7732.1606 - val_loss: 2493.5186 - val_root_mean_squared_error: 11721.2295\n",
      "Epoch 435/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2137.4392 - root_mean_squared_error: 7762.5269 - val_loss: 2473.8103 - val_root_mean_squared_error: 11684.0039\n",
      "Epoch 436/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2144.2654 - root_mean_squared_error: 7813.1436 - val_loss: 2489.3184 - val_root_mean_squared_error: 11568.9170\n",
      "Epoch 437/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2145.6577 - root_mean_squared_error: 7741.5308 - val_loss: 2485.5569 - val_root_mean_squared_error: 11766.0713\n",
      "Epoch 438/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2146.8337 - root_mean_squared_error: 7705.0425 - val_loss: 2515.7900 - val_root_mean_squared_error: 11430.6807\n",
      "Epoch 439/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2126.5229 - root_mean_squared_error: 7700.7803 - val_loss: 2463.3818 - val_root_mean_squared_error: 11540.2764\n",
      "Epoch 440/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2130.5750 - root_mean_squared_error: 7705.1714 - val_loss: 2466.6960 - val_root_mean_squared_error: 11359.3770\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 441/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2135.3223 - root_mean_squared_error: 7755.8105 - val_loss: 2457.4927 - val_root_mean_squared_error: 11557.6357\n",
      "Epoch 442/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2125.4624 - root_mean_squared_error: 7723.9619 - val_loss: 2464.5552 - val_root_mean_squared_error: 11492.8730\n",
      "Epoch 443/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2127.8801 - root_mean_squared_error: 7707.9326 - val_loss: 2481.7871 - val_root_mean_squared_error: 11288.6250\n",
      "Epoch 444/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2137.7488 - root_mean_squared_error: 7778.1392 - val_loss: 2445.1577 - val_root_mean_squared_error: 11537.2871\n",
      "Epoch 445/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2104.4124 - root_mean_squared_error: 7684.3555 - val_loss: 2444.8325 - val_root_mean_squared_error: 11277.1582\n",
      "Epoch 446/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2099.2041 - root_mean_squared_error: 7657.3101 - val_loss: 2439.6423 - val_root_mean_squared_error: 11418.2695\n",
      "Epoch 447/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2097.6816 - root_mean_squared_error: 7614.8618 - val_loss: 2435.2644 - val_root_mean_squared_error: 11276.6055\n",
      "Epoch 448/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2087.3586 - root_mean_squared_error: 7624.0889 - val_loss: 2427.3813 - val_root_mean_squared_error: 11217.8848\n",
      "Epoch 449/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2091.3389 - root_mean_squared_error: 7591.4961 - val_loss: 2416.5449 - val_root_mean_squared_error: 11273.0020\n",
      "Epoch 450/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2089.5410 - root_mean_squared_error: 7611.4888 - val_loss: 2433.9321 - val_root_mean_squared_error: 11086.3389\n",
      "Epoch 451/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2084.2202 - root_mean_squared_error: 7592.1562 - val_loss: 2405.6003 - val_root_mean_squared_error: 11184.1172\n",
      "Epoch 452/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2072.4221 - root_mean_squared_error: 7597.7437 - val_loss: 2411.2107 - val_root_mean_squared_error: 11040.0898\n",
      "Epoch 453/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2067.7527 - root_mean_squared_error: 7583.7485 - val_loss: 2396.9810 - val_root_mean_squared_error: 11171.4189\n",
      "Epoch 454/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2070.8191 - root_mean_squared_error: 7617.7397 - val_loss: 2407.8540 - val_root_mean_squared_error: 11042.7402\n",
      "Epoch 455/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2067.6125 - root_mean_squared_error: 7590.3804 - val_loss: 2394.7771 - val_root_mean_squared_error: 10981.2812\n",
      "Epoch 456/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2063.2441 - root_mean_squared_error: 7558.5146 - val_loss: 2384.4702 - val_root_mean_squared_error: 11035.1514\n",
      "Epoch 457/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2056.4077 - root_mean_squared_error: 7562.7939 - val_loss: 2374.7551 - val_root_mean_squared_error: 10946.4033\n",
      "Epoch 458/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2058.9902 - root_mean_squared_error: 7632.6079 - val_loss: 2378.6909 - val_root_mean_squared_error: 10986.7354\n",
      "Epoch 459/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2040.7311 - root_mean_squared_error: 7589.5225 - val_loss: 2372.8713 - val_root_mean_squared_error: 11202.7637\n",
      "Epoch 460/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2050.9355 - root_mean_squared_error: 7601.3472 - val_loss: 2376.3606 - val_root_mean_squared_error: 10952.9736\n",
      "Epoch 461/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2051.3831 - root_mean_squared_error: 7558.7891 - val_loss: 2364.2209 - val_root_mean_squared_error: 11056.1182\n",
      "Epoch 462/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2042.7903 - root_mean_squared_error: 7655.8486 - val_loss: 2370.5068 - val_root_mean_squared_error: 11272.1260\n",
      "Epoch 463/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2040.0867 - root_mean_squared_error: 7603.9336 - val_loss: 2366.2607 - val_root_mean_squared_error: 11005.1865\n",
      "Epoch 464/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2035.7010 - root_mean_squared_error: 7526.3838 - val_loss: 2366.8567 - val_root_mean_squared_error: 11163.6055\n",
      "Epoch 465/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2051.8806 - root_mean_squared_error: 7540.0479 - val_loss: 2354.0349 - val_root_mean_squared_error: 11009.4434\n",
      "Epoch 466/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2026.2919 - root_mean_squared_error: 7571.7222 - val_loss: 2344.0427 - val_root_mean_squared_error: 10972.3242\n",
      "Epoch 467/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2062.2166 - root_mean_squared_error: 7573.6865 - val_loss: 2346.2661 - val_root_mean_squared_error: 11182.0781\n",
      "Epoch 468/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2042.0685 - root_mean_squared_error: 7597.4077 - val_loss: 2342.0190 - val_root_mean_squared_error: 11103.7861\n",
      "Epoch 469/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2024.8171 - root_mean_squared_error: 7592.3682 - val_loss: 2324.5874 - val_root_mean_squared_error: 11100.3662\n",
      "Epoch 470/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2016.2909 - root_mean_squared_error: 7576.3706 - val_loss: 2353.6775 - val_root_mean_squared_error: 10996.3779\n",
      "Epoch 471/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2021.2241 - root_mean_squared_error: 7557.3003 - val_loss: 2350.8079 - val_root_mean_squared_error: 10909.3096\n",
      "Epoch 472/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2022.8351 - root_mean_squared_error: 7545.3423 - val_loss: 2323.9890 - val_root_mean_squared_error: 11072.9336\n",
      "Epoch 473/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2027.3503 - root_mean_squared_error: 7584.0195 - val_loss: 2350.3210 - val_root_mean_squared_error: 10968.2373\n",
      "Epoch 474/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2015.6615 - root_mean_squared_error: 7574.9517 - val_loss: 2334.1760 - val_root_mean_squared_error: 11131.1260\n",
      "Epoch 475/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2026.0798 - root_mean_squared_error: 7651.5127 - val_loss: 2363.8784 - val_root_mean_squared_error: 10952.3350\n",
      "Epoch 476/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2015.7209 - root_mean_squared_error: 7553.0278 - val_loss: 2335.9612 - val_root_mean_squared_error: 11078.4873\n",
      "Epoch 477/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2013.7068 - root_mean_squared_error: 7547.8901 - val_loss: 2318.4919 - val_root_mean_squared_error: 10927.8477\n",
      "Epoch 478/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2014.5956 - root_mean_squared_error: 7501.5698 - val_loss: 2322.2734 - val_root_mean_squared_error: 10948.1045\n",
      "Epoch 479/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2014.1864 - root_mean_squared_error: 7568.7700 - val_loss: 2319.3604 - val_root_mean_squared_error: 11019.5703\n",
      "Epoch 480/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2001.4619 - root_mean_squared_error: 7574.1772 - val_loss: 2320.1375 - val_root_mean_squared_error: 10926.0947\n",
      "Epoch 481/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2011.9102 - root_mean_squared_error: 7600.2168 - val_loss: 2310.7434 - val_root_mean_squared_error: 11046.8955\n",
      "Epoch 482/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2024.0796 - root_mean_squared_error: 7585.4912 - val_loss: 2301.4993 - val_root_mean_squared_error: 10845.3916\n",
      "Epoch 483/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2005.9041 - root_mean_squared_error: 7535.9790 - val_loss: 2297.2402 - val_root_mean_squared_error: 10955.6992\n",
      "Epoch 484/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2009.4962 - root_mean_squared_error: 7573.2026 - val_loss: 2330.7900 - val_root_mean_squared_error: 11034.6016\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 485/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2014.3018 - root_mean_squared_error: 7584.3525 - val_loss: 2324.2627 - val_root_mean_squared_error: 11201.0303\n",
      "Epoch 486/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2011.8574 - root_mean_squared_error: 7578.0298 - val_loss: 2316.1909 - val_root_mean_squared_error: 11140.1738\n",
      "Epoch 487/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1995.0055 - root_mean_squared_error: 7560.7441 - val_loss: 2304.3962 - val_root_mean_squared_error: 10837.0576\n",
      "Epoch 488/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2000.8654 - root_mean_squared_error: 7528.5669 - val_loss: 2299.9373 - val_root_mean_squared_error: 10771.5439\n",
      "Epoch 489/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2008.7848 - root_mean_squared_error: 7574.7446 - val_loss: 2312.0767 - val_root_mean_squared_error: 10920.2402\n",
      "Epoch 490/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1997.9067 - root_mean_squared_error: 7539.8789 - val_loss: 2300.7747 - val_root_mean_squared_error: 10969.9717\n",
      "Epoch 491/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1993.7828 - root_mean_squared_error: 7548.6270 - val_loss: 2295.7385 - val_root_mean_squared_error: 10949.1514\n",
      "Epoch 492/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2003.6464 - root_mean_squared_error: 7608.4473 - val_loss: 2311.9558 - val_root_mean_squared_error: 11079.3486\n",
      "Epoch 493/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1983.2133 - root_mean_squared_error: 7544.1484 - val_loss: 2312.0420 - val_root_mean_squared_error: 10831.7354\n",
      "Epoch 494/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2000.8018 - root_mean_squared_error: 7488.5518 - val_loss: 2285.5012 - val_root_mean_squared_error: 10885.5312\n",
      "Epoch 495/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2020.4998 - root_mean_squared_error: 7582.9282 - val_loss: 2333.4294 - val_root_mean_squared_error: 10840.7656\n",
      "Epoch 496/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1998.6090 - root_mean_squared_error: 7523.8291 - val_loss: 2316.4648 - val_root_mean_squared_error: 10993.8262\n",
      "Epoch 497/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2015.3395 - root_mean_squared_error: 7543.1553 - val_loss: 2305.9128 - val_root_mean_squared_error: 10917.7041\n",
      "Epoch 498/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2010.0247 - root_mean_squared_error: 7565.6587 - val_loss: 2339.3667 - val_root_mean_squared_error: 10744.5283\n",
      "Epoch 499/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2014.5690 - root_mean_squared_error: 7500.0884 - val_loss: 2326.2656 - val_root_mean_squared_error: 11055.3467\n",
      "Epoch 500/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2016.4418 - root_mean_squared_error: 7517.4971 - val_loss: 2320.4939 - val_root_mean_squared_error: 10619.7842\n",
      "Epoch 501/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2008.1321 - root_mean_squared_error: 7631.1553 - val_loss: 2267.7644 - val_root_mean_squared_error: 10821.0186\n",
      "Epoch 502/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1999.5150 - root_mean_squared_error: 7480.0454 - val_loss: 2290.6008 - val_root_mean_squared_error: 10924.8936\n",
      "Epoch 503/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2030.2433 - root_mean_squared_error: 7579.7998 - val_loss: 2272.8916 - val_root_mean_squared_error: 10691.1191\n",
      "Epoch 504/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1987.0089 - root_mean_squared_error: 7511.7544 - val_loss: 2283.5747 - val_root_mean_squared_error: 10752.2363\n",
      "Epoch 505/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1990.3708 - root_mean_squared_error: 7498.3491 - val_loss: 2271.9973 - val_root_mean_squared_error: 10869.0020\n",
      "Epoch 506/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1981.7379 - root_mean_squared_error: 7531.9717 - val_loss: 2289.4412 - val_root_mean_squared_error: 10794.1465\n",
      "Epoch 507/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1976.6893 - root_mean_squared_error: 7564.1650 - val_loss: 2254.2214 - val_root_mean_squared_error: 10927.4199\n",
      "Epoch 508/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1975.5271 - root_mean_squared_error: 7518.2036 - val_loss: 2271.9341 - val_root_mean_squared_error: 10797.3818\n",
      "Epoch 509/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1974.3993 - root_mean_squared_error: 7511.3604 - val_loss: 2257.3047 - val_root_mean_squared_error: 10905.0762\n",
      "Epoch 510/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1990.4204 - root_mean_squared_error: 7585.1826 - val_loss: 2260.4429 - val_root_mean_squared_error: 10809.8691\n",
      "Epoch 511/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1971.5873 - root_mean_squared_error: 7535.2422 - val_loss: 2276.4421 - val_root_mean_squared_error: 10763.7334\n",
      "Epoch 512/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1969.4016 - root_mean_squared_error: 7526.7266 - val_loss: 2263.5396 - val_root_mean_squared_error: 10815.9170\n",
      "Epoch 513/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1983.5695 - root_mean_squared_error: 7640.7339 - val_loss: 2254.4746 - val_root_mean_squared_error: 11037.3818\n",
      "Epoch 514/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1972.2285 - root_mean_squared_error: 7496.6074 - val_loss: 2286.4810 - val_root_mean_squared_error: 10711.4678\n",
      "Epoch 515/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1975.9072 - root_mean_squared_error: 7477.4229 - val_loss: 2252.9463 - val_root_mean_squared_error: 10694.3447\n",
      "Epoch 516/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1973.1311 - root_mean_squared_error: 7470.0581 - val_loss: 2247.7864 - val_root_mean_squared_error: 10692.0615\n",
      "Epoch 517/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1973.6991 - root_mean_squared_error: 7518.3003 - val_loss: 2261.9551 - val_root_mean_squared_error: 10957.1533\n",
      "Epoch 518/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1990.5764 - root_mean_squared_error: 7586.0562 - val_loss: 2315.5186 - val_root_mean_squared_error: 10552.1006\n",
      "Epoch 519/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2002.8123 - root_mean_squared_error: 7422.2290 - val_loss: 2282.2683 - val_root_mean_squared_error: 10736.1035\n",
      "Epoch 520/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1989.4058 - root_mean_squared_error: 7526.9644 - val_loss: 2254.6726 - val_root_mean_squared_error: 10832.1094\n",
      "Epoch 521/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1984.0573 - root_mean_squared_error: 7565.0093 - val_loss: 2256.4260 - val_root_mean_squared_error: 10700.7178\n",
      "Epoch 522/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1967.9150 - root_mean_squared_error: 7491.2437 - val_loss: 2238.3147 - val_root_mean_squared_error: 10727.8984\n",
      "Epoch 523/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1968.9755 - root_mean_squared_error: 7485.1030 - val_loss: 2233.8008 - val_root_mean_squared_error: 10812.8154\n",
      "Epoch 524/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1971.1169 - root_mean_squared_error: 7486.2280 - val_loss: 2306.1094 - val_root_mean_squared_error: 10494.7324\n",
      "Epoch 525/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2008.0188 - root_mean_squared_error: 7503.9771 - val_loss: 2271.5972 - val_root_mean_squared_error: 10798.3818\n",
      "Epoch 526/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 2009.9753 - root_mean_squared_error: 7507.4902 - val_loss: 2222.6284 - val_root_mean_squared_error: 10737.4922\n",
      "Epoch 527/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1985.4127 - root_mean_squared_error: 7574.4541 - val_loss: 2287.5432 - val_root_mean_squared_error: 10481.2920\n",
      "Epoch 528/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1976.1528 - root_mean_squared_error: 7492.8379 - val_loss: 2227.9492 - val_root_mean_squared_error: 10717.8691\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 529/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1966.7662 - root_mean_squared_error: 7515.6978 - val_loss: 2257.5100 - val_root_mean_squared_error: 10664.5391\n",
      "Epoch 530/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1969.0770 - root_mean_squared_error: 7503.3364 - val_loss: 2233.1487 - val_root_mean_squared_error: 10626.8154\n",
      "Epoch 531/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1957.7621 - root_mean_squared_error: 7489.8931 - val_loss: 2209.0923 - val_root_mean_squared_error: 10700.6084\n",
      "Epoch 532/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1968.0845 - root_mean_squared_error: 7522.1646 - val_loss: 2267.0757 - val_root_mean_squared_error: 10399.5479\n",
      "Epoch 533/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1997.3986 - root_mean_squared_error: 7487.8945 - val_loss: 2221.4741 - val_root_mean_squared_error: 10644.2480\n",
      "Epoch 534/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1995.8845 - root_mean_squared_error: 7485.2061 - val_loss: 2230.7566 - val_root_mean_squared_error: 10566.2617\n",
      "Epoch 535/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1960.9806 - root_mean_squared_error: 7504.3525 - val_loss: 2224.5056 - val_root_mean_squared_error: 10697.0830\n",
      "Epoch 536/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1967.4729 - root_mean_squared_error: 7536.5991 - val_loss: 2219.5166 - val_root_mean_squared_error: 10801.9941\n",
      "Epoch 537/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1957.9050 - root_mean_squared_error: 7512.9067 - val_loss: 2221.7466 - val_root_mean_squared_error: 10727.2148\n",
      "Epoch 538/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1955.5400 - root_mean_squared_error: 7535.3984 - val_loss: 2236.4031 - val_root_mean_squared_error: 10587.4209\n",
      "Epoch 539/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1965.1176 - root_mean_squared_error: 7488.5991 - val_loss: 2229.4429 - val_root_mean_squared_error: 10554.9658\n",
      "Epoch 540/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1956.8168 - root_mean_squared_error: 7513.4897 - val_loss: 2223.1240 - val_root_mean_squared_error: 10715.1816\n",
      "Epoch 541/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1964.8914 - root_mean_squared_error: 7547.7666 - val_loss: 2218.1929 - val_root_mean_squared_error: 10827.6553\n",
      "Epoch 542/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1959.8197 - root_mean_squared_error: 7534.3433 - val_loss: 2233.2930 - val_root_mean_squared_error: 10641.7148\n",
      "Epoch 543/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1953.5048 - root_mean_squared_error: 7494.0713 - val_loss: 2221.1501 - val_root_mean_squared_error: 10624.6992\n",
      "Epoch 544/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1949.0585 - root_mean_squared_error: 7508.0361 - val_loss: 2207.5137 - val_root_mean_squared_error: 10649.3203\n",
      "Epoch 545/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1950.1097 - root_mean_squared_error: 7501.5728 - val_loss: 2218.1492 - val_root_mean_squared_error: 10627.1201\n",
      "Epoch 546/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1950.8035 - root_mean_squared_error: 7511.5933 - val_loss: 2210.7134 - val_root_mean_squared_error: 10680.2588\n",
      "Epoch 547/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1958.5375 - root_mean_squared_error: 7496.3232 - val_loss: 2208.8540 - val_root_mean_squared_error: 10732.8975\n",
      "Epoch 548/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1955.3009 - root_mean_squared_error: 7514.5117 - val_loss: 2231.6143 - val_root_mean_squared_error: 10574.6992\n",
      "Epoch 549/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1959.6899 - root_mean_squared_error: 7497.2905 - val_loss: 2205.3916 - val_root_mean_squared_error: 10639.0000\n",
      "Epoch 550/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1949.4460 - root_mean_squared_error: 7506.8330 - val_loss: 2196.5151 - val_root_mean_squared_error: 10734.4600\n",
      "Epoch 551/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1964.9115 - root_mean_squared_error: 7546.8882 - val_loss: 2206.2229 - val_root_mean_squared_error: 10516.5840\n",
      "Epoch 552/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1957.2004 - root_mean_squared_error: 7491.3452 - val_loss: 2191.8215 - val_root_mean_squared_error: 10503.7520\n",
      "Epoch 553/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1958.6945 - root_mean_squared_error: 7504.0029 - val_loss: 2227.3079 - val_root_mean_squared_error: 10492.4990\n",
      "Epoch 554/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1955.0488 - root_mean_squared_error: 7469.1226 - val_loss: 2195.4829 - val_root_mean_squared_error: 10678.2227\n",
      "Epoch 555/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1957.5406 - root_mean_squared_error: 7535.6665 - val_loss: 2200.6011 - val_root_mean_squared_error: 10663.2568\n",
      "Epoch 556/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1968.2225 - root_mean_squared_error: 7557.5444 - val_loss: 2214.4490 - val_root_mean_squared_error: 10522.6602\n",
      "Epoch 557/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1975.0530 - root_mean_squared_error: 7458.1353 - val_loss: 2207.4221 - val_root_mean_squared_error: 10635.5449\n",
      "Epoch 558/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1982.3462 - root_mean_squared_error: 7539.6514 - val_loss: 2193.1035 - val_root_mean_squared_error: 10471.1914\n",
      "Epoch 559/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1951.4198 - root_mean_squared_error: 7489.3184 - val_loss: 2217.4268 - val_root_mean_squared_error: 10574.9111\n",
      "Epoch 560/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1958.1366 - root_mean_squared_error: 7523.3608 - val_loss: 2215.6533 - val_root_mean_squared_error: 10569.3887\n",
      "Epoch 561/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1964.9528 - root_mean_squared_error: 7498.9253 - val_loss: 2222.5596 - val_root_mean_squared_error: 10682.9648\n",
      "Epoch 562/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2027.5470 - root_mean_squared_error: 7555.3657 - val_loss: 2211.1711 - val_root_mean_squared_error: 10376.9043\n",
      "Epoch 563/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1976.0132 - root_mean_squared_error: 7490.5142 - val_loss: 2216.1250 - val_root_mean_squared_error: 10526.0156\n",
      "Epoch 564/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1943.8669 - root_mean_squared_error: 7499.1626 - val_loss: 2207.1592 - val_root_mean_squared_error: 10561.1084\n",
      "Epoch 565/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1947.4153 - root_mean_squared_error: 7513.4653 - val_loss: 2206.5281 - val_root_mean_squared_error: 10622.0215\n",
      "Epoch 566/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1946.9572 - root_mean_squared_error: 7515.1211 - val_loss: 2204.3591 - val_root_mean_squared_error: 10503.4482\n",
      "Epoch 567/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1947.1118 - root_mean_squared_error: 7480.9302 - val_loss: 2183.8618 - val_root_mean_squared_error: 10497.9902\n",
      "Epoch 568/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1955.8462 - root_mean_squared_error: 7514.5830 - val_loss: 2177.2559 - val_root_mean_squared_error: 10681.4785\n",
      "Epoch 569/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1970.6046 - root_mean_squared_error: 7557.4668 - val_loss: 2238.8425 - val_root_mean_squared_error: 10260.4824\n",
      "Epoch 570/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1981.7999 - root_mean_squared_error: 7466.2490 - val_loss: 2181.9153 - val_root_mean_squared_error: 10335.0195\n",
      "Epoch 571/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1951.5297 - root_mean_squared_error: 7436.9961 - val_loss: 2184.3325 - val_root_mean_squared_error: 10582.2119\n",
      "Epoch 572/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1964.6033 - root_mean_squared_error: 7494.1279 - val_loss: 2187.9565 - val_root_mean_squared_error: 10546.9014\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 573/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1953.3478 - root_mean_squared_error: 7549.7163 - val_loss: 2194.6436 - val_root_mean_squared_error: 10519.3545\n",
      "Epoch 574/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1985.3466 - root_mean_squared_error: 7481.0322 - val_loss: 2225.6941 - val_root_mean_squared_error: 10633.4844\n",
      "Epoch 575/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1992.6473 - root_mean_squared_error: 7481.7441 - val_loss: 2244.3203 - val_root_mean_squared_error: 10274.7295\n",
      "Epoch 576/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1976.9814 - root_mean_squared_error: 7451.0498 - val_loss: 2194.1248 - val_root_mean_squared_error: 10531.7939\n",
      "Epoch 577/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1955.0413 - root_mean_squared_error: 7489.9561 - val_loss: 2181.9990 - val_root_mean_squared_error: 10439.1289\n",
      "Epoch 578/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1940.2312 - root_mean_squared_error: 7476.5713 - val_loss: 2195.3762 - val_root_mean_squared_error: 10407.6787\n",
      "Epoch 579/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1962.4319 - root_mean_squared_error: 7434.1616 - val_loss: 2195.3306 - val_root_mean_squared_error: 10586.4531\n",
      "Epoch 580/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1965.9838 - root_mean_squared_error: 7493.3716 - val_loss: 2182.3113 - val_root_mean_squared_error: 10429.2949\n",
      "Epoch 581/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1950.5142 - root_mean_squared_error: 7487.1123 - val_loss: 2173.1082 - val_root_mean_squared_error: 10556.5791\n",
      "Epoch 582/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1949.3597 - root_mean_squared_error: 7496.8076 - val_loss: 2177.1460 - val_root_mean_squared_error: 10666.6123\n",
      "Epoch 583/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1948.1531 - root_mean_squared_error: 7519.7432 - val_loss: 2185.0559 - val_root_mean_squared_error: 10412.8506\n",
      "Epoch 584/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1946.9719 - root_mean_squared_error: 7484.3721 - val_loss: 2173.7395 - val_root_mean_squared_error: 10567.9277\n",
      "Epoch 585/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1942.2810 - root_mean_squared_error: 7494.9805 - val_loss: 2183.4333 - val_root_mean_squared_error: 10492.8828\n",
      "Epoch 586/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1940.0410 - root_mean_squared_error: 7497.5308 - val_loss: 2183.1135 - val_root_mean_squared_error: 10514.2266\n",
      "Epoch 587/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1941.9620 - root_mean_squared_error: 7500.7197 - val_loss: 2180.2642 - val_root_mean_squared_error: 10537.4219\n",
      "Epoch 588/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.6521 - root_mean_squared_error: 7478.1060 - val_loss: 2193.2600 - val_root_mean_squared_error: 10449.5596\n",
      "Epoch 589/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1947.5950 - root_mean_squared_error: 7491.3726 - val_loss: 2199.9087 - val_root_mean_squared_error: 10430.5508\n",
      "Epoch 590/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1966.2660 - root_mean_squared_error: 7547.4023 - val_loss: 2172.4326 - val_root_mean_squared_error: 10682.9473\n",
      "Epoch 591/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1980.8008 - root_mean_squared_error: 7581.3896 - val_loss: 2198.5725 - val_root_mean_squared_error: 10604.9141\n",
      "Epoch 592/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1974.2506 - root_mean_squared_error: 7548.5244 - val_loss: 2198.0061 - val_root_mean_squared_error: 10328.3779\n",
      "Epoch 593/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1961.9537 - root_mean_squared_error: 7508.1421 - val_loss: 2171.5903 - val_root_mean_squared_error: 10404.4629\n",
      "Epoch 594/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1942.8831 - root_mean_squared_error: 7463.2446 - val_loss: 2185.3611 - val_root_mean_squared_error: 10452.3691\n",
      "Epoch 595/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1942.6473 - root_mean_squared_error: 7463.8569 - val_loss: 2178.9043 - val_root_mean_squared_error: 10606.6250\n",
      "Epoch 596/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1951.4562 - root_mean_squared_error: 7499.7983 - val_loss: 2176.3916 - val_root_mean_squared_error: 10569.1631\n",
      "Epoch 597/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1953.8276 - root_mean_squared_error: 7491.8672 - val_loss: 2187.6138 - val_root_mean_squared_error: 10368.0020\n",
      "Epoch 598/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1946.8970 - root_mean_squared_error: 7478.9780 - val_loss: 2168.4539 - val_root_mean_squared_error: 10479.4287\n",
      "Epoch 599/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1940.6582 - root_mean_squared_error: 7485.7207 - val_loss: 2170.5378 - val_root_mean_squared_error: 10491.4854\n",
      "Epoch 600/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1944.1064 - root_mean_squared_error: 7481.4199 - val_loss: 2169.4412 - val_root_mean_squared_error: 10544.9336\n",
      "Epoch 601/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1944.7494 - root_mean_squared_error: 7551.5869 - val_loss: 2169.2290 - val_root_mean_squared_error: 10674.3564\n",
      "Epoch 602/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1948.5819 - root_mean_squared_error: 7493.3828 - val_loss: 2207.8752 - val_root_mean_squared_error: 10379.2178\n",
      "Epoch 603/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1944.5034 - root_mean_squared_error: 7506.1895 - val_loss: 2175.4717 - val_root_mean_squared_error: 10511.3145\n",
      "Epoch 604/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1949.9556 - root_mean_squared_error: 7489.8701 - val_loss: 2173.5469 - val_root_mean_squared_error: 10535.3848\n",
      "Epoch 605/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1940.5754 - root_mean_squared_error: 7495.7036 - val_loss: 2169.9519 - val_root_mean_squared_error: 10528.3154\n",
      "Epoch 606/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1933.0173 - root_mean_squared_error: 7487.2593 - val_loss: 2177.9719 - val_root_mean_squared_error: 10428.0088\n",
      "Epoch 607/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.1116 - root_mean_squared_error: 7464.3359 - val_loss: 2165.5420 - val_root_mean_squared_error: 10466.3779\n",
      "Epoch 608/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1952.4031 - root_mean_squared_error: 7521.5596 - val_loss: 2167.1570 - val_root_mean_squared_error: 10572.1562\n",
      "Epoch 609/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1943.5150 - root_mean_squared_error: 7486.0132 - val_loss: 2224.9929 - val_root_mean_squared_error: 10226.0283\n",
      "Epoch 610/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1964.4105 - root_mean_squared_error: 7406.8384 - val_loss: 2164.4426 - val_root_mean_squared_error: 10376.4082\n",
      "Epoch 611/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1950.5787 - root_mean_squared_error: 7464.4829 - val_loss: 2165.1797 - val_root_mean_squared_error: 10501.8203\n",
      "Epoch 612/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1947.6234 - root_mean_squared_error: 7485.3159 - val_loss: 2174.5178 - val_root_mean_squared_error: 10490.8730\n",
      "Epoch 613/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1935.5786 - root_mean_squared_error: 7515.6860 - val_loss: 2183.1741 - val_root_mean_squared_error: 10560.0811\n",
      "Epoch 614/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1939.6816 - root_mean_squared_error: 7471.8359 - val_loss: 2179.2051 - val_root_mean_squared_error: 10510.0059\n",
      "Epoch 615/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1936.9840 - root_mean_squared_error: 7502.2461 - val_loss: 2176.1729 - val_root_mean_squared_error: 10342.4873\n",
      "Epoch 616/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1938.1471 - root_mean_squared_error: 7503.5498 - val_loss: 2164.9592 - val_root_mean_squared_error: 10523.2881\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 617/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1950.9015 - root_mean_squared_error: 7488.3569 - val_loss: 2170.5457 - val_root_mean_squared_error: 10663.4248\n",
      "Epoch 618/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1962.2749 - root_mean_squared_error: 7550.1577 - val_loss: 2216.3047 - val_root_mean_squared_error: 10322.1172\n",
      "Epoch 619/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1957.6077 - root_mean_squared_error: 7505.4941 - val_loss: 2167.8120 - val_root_mean_squared_error: 10605.0527\n",
      "Epoch 620/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1929.7627 - root_mean_squared_error: 7460.8584 - val_loss: 2191.9316 - val_root_mean_squared_error: 10399.3291\n",
      "Epoch 621/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1954.4281 - root_mean_squared_error: 7532.3828 - val_loss: 2206.5276 - val_root_mean_squared_error: 10337.0850\n",
      "Epoch 622/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1959.7184 - root_mean_squared_error: 7445.2720 - val_loss: 2176.3850 - val_root_mean_squared_error: 10547.4736\n",
      "Epoch 623/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1945.7251 - root_mean_squared_error: 7444.6079 - val_loss: 2168.6062 - val_root_mean_squared_error: 10533.0771\n",
      "Epoch 624/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1948.8567 - root_mean_squared_error: 7501.3486 - val_loss: 2186.0374 - val_root_mean_squared_error: 10273.1660\n",
      "Epoch 625/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1967.0300 - root_mean_squared_error: 7544.5327 - val_loss: 2166.1326 - val_root_mean_squared_error: 10420.1055\n",
      "Epoch 626/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1946.3380 - root_mean_squared_error: 7502.5210 - val_loss: 2170.2922 - val_root_mean_squared_error: 10417.3164\n",
      "Epoch 627/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.1163 - root_mean_squared_error: 7471.1016 - val_loss: 2178.6868 - val_root_mean_squared_error: 10555.2129\n",
      "Epoch 628/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1941.7346 - root_mean_squared_error: 7469.9268 - val_loss: 2179.4609 - val_root_mean_squared_error: 10441.1865\n",
      "Epoch 629/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.3286 - root_mean_squared_error: 7500.8081 - val_loss: 2186.0796 - val_root_mean_squared_error: 10364.1396\n",
      "Epoch 630/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1946.4998 - root_mean_squared_error: 7457.8096 - val_loss: 2170.5046 - val_root_mean_squared_error: 10477.5117\n",
      "Epoch 631/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1947.0099 - root_mean_squared_error: 7496.3408 - val_loss: 2164.8936 - val_root_mean_squared_error: 10505.7031\n",
      "Epoch 632/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1945.1470 - root_mean_squared_error: 7517.8608 - val_loss: 2214.5906 - val_root_mean_squared_error: 10122.8564\n",
      "Epoch 633/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1964.7972 - root_mean_squared_error: 7435.9321 - val_loss: 2171.4290 - val_root_mean_squared_error: 10318.4883\n",
      "Epoch 634/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1945.5229 - root_mean_squared_error: 7449.1357 - val_loss: 2156.8477 - val_root_mean_squared_error: 10425.3096\n",
      "Epoch 635/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1936.2657 - root_mean_squared_error: 7488.6562 - val_loss: 2164.6919 - val_root_mean_squared_error: 10493.6543\n",
      "Epoch 636/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1939.0695 - root_mean_squared_error: 7470.9194 - val_loss: 2176.3403 - val_root_mean_squared_error: 10580.6904\n",
      "Epoch 637/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1951.3737 - root_mean_squared_error: 7533.5127 - val_loss: 2171.0938 - val_root_mean_squared_error: 10362.8760\n",
      "Epoch 638/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1947.2900 - root_mean_squared_error: 7526.8301 - val_loss: 2170.0015 - val_root_mean_squared_error: 10433.7578\n",
      "Epoch 639/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1958.4882 - root_mean_squared_error: 7539.6763 - val_loss: 2184.3550 - val_root_mean_squared_error: 10666.5391\n",
      "Epoch 640/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1958.4739 - root_mean_squared_error: 7511.7817 - val_loss: 2195.7957 - val_root_mean_squared_error: 10353.5234\n",
      "Epoch 641/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1936.1029 - root_mean_squared_error: 7471.4521 - val_loss: 2164.3945 - val_root_mean_squared_error: 10366.8730\n",
      "Epoch 642/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1941.5482 - root_mean_squared_error: 7473.3203 - val_loss: 2171.4543 - val_root_mean_squared_error: 10569.2188\n",
      "Epoch 643/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1942.6943 - root_mean_squared_error: 7435.8975 - val_loss: 2178.6858 - val_root_mean_squared_error: 10229.8740\n",
      "Epoch 644/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1937.4078 - root_mean_squared_error: 7465.4224 - val_loss: 2147.1997 - val_root_mean_squared_error: 10320.4062\n",
      "Epoch 645/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1931.5778 - root_mean_squared_error: 7465.5576 - val_loss: 2162.3306 - val_root_mean_squared_error: 10446.8682\n",
      "Epoch 646/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1957.7111 - root_mean_squared_error: 7515.2158 - val_loss: 2187.8533 - val_root_mean_squared_error: 10120.1387\n",
      "Epoch 647/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1954.0297 - root_mean_squared_error: 7448.9785 - val_loss: 2159.4504 - val_root_mean_squared_error: 10293.2607\n",
      "Epoch 648/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1935.6547 - root_mean_squared_error: 7462.8726 - val_loss: 2156.1345 - val_root_mean_squared_error: 10440.1377\n",
      "Epoch 649/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1931.7516 - root_mean_squared_error: 7478.8716 - val_loss: 2151.7261 - val_root_mean_squared_error: 10426.9668\n",
      "Epoch 650/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1944.4805 - root_mean_squared_error: 7560.7832 - val_loss: 2195.8098 - val_root_mean_squared_error: 10341.2490\n",
      "Epoch 651/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1943.3195 - root_mean_squared_error: 7470.9409 - val_loss: 2169.6143 - val_root_mean_squared_error: 10385.2910\n",
      "Epoch 652/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1932.9303 - root_mean_squared_error: 7444.8735 - val_loss: 2151.4343 - val_root_mean_squared_error: 10455.0254\n",
      "Epoch 653/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1932.8019 - root_mean_squared_error: 7508.3994 - val_loss: 2156.5688 - val_root_mean_squared_error: 10432.5020\n",
      "Epoch 654/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1932.3392 - root_mean_squared_error: 7475.9263 - val_loss: 2163.9753 - val_root_mean_squared_error: 10420.9248\n",
      "Epoch 655/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1947.5841 - root_mean_squared_error: 7551.3501 - val_loss: 2182.9907 - val_root_mean_squared_error: 10291.5127\n",
      "Epoch 656/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1937.3329 - root_mean_squared_error: 7520.8574 - val_loss: 2156.8267 - val_root_mean_squared_error: 10448.2617\n",
      "Epoch 657/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1933.6588 - root_mean_squared_error: 7505.6128 - val_loss: 2162.4963 - val_root_mean_squared_error: 10446.2471\n",
      "Epoch 658/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1942.4858 - root_mean_squared_error: 7421.7012 - val_loss: 2178.4360 - val_root_mean_squared_error: 10053.6650\n",
      "Epoch 659/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1945.6212 - root_mean_squared_error: 7422.4082 - val_loss: 2146.7397 - val_root_mean_squared_error: 10206.0654\n",
      "Epoch 660/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1948.3815 - root_mean_squared_error: 7531.2622 - val_loss: 2157.9209 - val_root_mean_squared_error: 10386.5586\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 661/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1939.4738 - root_mean_squared_error: 7500.3208 - val_loss: 2165.2378 - val_root_mean_squared_error: 10488.1807\n",
      "Epoch 662/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.1096 - root_mean_squared_error: 7464.8413 - val_loss: 2180.9573 - val_root_mean_squared_error: 10280.1924\n",
      "Epoch 663/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1943.2798 - root_mean_squared_error: 7470.3267 - val_loss: 2169.2065 - val_root_mean_squared_error: 10314.2803\n",
      "Epoch 664/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1940.2849 - root_mean_squared_error: 7504.7598 - val_loss: 2143.1086 - val_root_mean_squared_error: 10454.8838\n",
      "Epoch 665/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1936.8268 - root_mean_squared_error: 7506.0137 - val_loss: 2157.6240 - val_root_mean_squared_error: 10405.8330\n",
      "Epoch 666/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1951.0828 - root_mean_squared_error: 7520.8037 - val_loss: 2211.4966 - val_root_mean_squared_error: 10387.7549\n",
      "Epoch 667/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1960.0035 - root_mean_squared_error: 7592.9497 - val_loss: 2180.3750 - val_root_mean_squared_error: 10803.6543\n",
      "Epoch 668/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1959.7820 - root_mean_squared_error: 7491.4619 - val_loss: 2198.8831 - val_root_mean_squared_error: 10434.9307\n",
      "Epoch 669/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1945.6486 - root_mean_squared_error: 7482.2139 - val_loss: 2158.4207 - val_root_mean_squared_error: 10314.1436\n",
      "Epoch 670/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1955.8456 - root_mean_squared_error: 7448.8994 - val_loss: 2164.9968 - val_root_mean_squared_error: 10347.8535\n",
      "Epoch 671/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1971.6403 - root_mean_squared_error: 7487.3140 - val_loss: 2169.1528 - val_root_mean_squared_error: 10145.7803\n",
      "Epoch 672/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.2928 - root_mean_squared_error: 7462.3765 - val_loss: 2169.7134 - val_root_mean_squared_error: 10463.9033\n",
      "Epoch 673/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1943.7640 - root_mean_squared_error: 7485.9795 - val_loss: 2162.6458 - val_root_mean_squared_error: 10447.8779\n",
      "Epoch 674/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1929.2988 - root_mean_squared_error: 7470.7490 - val_loss: 2171.0930 - val_root_mean_squared_error: 10268.8252\n",
      "Epoch 675/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1933.3124 - root_mean_squared_error: 7428.2051 - val_loss: 2151.9265 - val_root_mean_squared_error: 10308.9141\n",
      "Epoch 676/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1932.5220 - root_mean_squared_error: 7499.0649 - val_loss: 2156.4333 - val_root_mean_squared_error: 10378.7256\n",
      "Epoch 677/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1945.6189 - root_mean_squared_error: 7502.8467 - val_loss: 2159.2429 - val_root_mean_squared_error: 10518.2266\n",
      "Epoch 678/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1936.2164 - root_mean_squared_error: 7510.4531 - val_loss: 2175.5569 - val_root_mean_squared_error: 10395.3994\n",
      "Epoch 679/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1942.7830 - root_mean_squared_error: 7495.7827 - val_loss: 2156.2412 - val_root_mean_squared_error: 10469.4990\n",
      "Epoch 680/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1935.0166 - root_mean_squared_error: 7454.8174 - val_loss: 2156.1814 - val_root_mean_squared_error: 10393.7725\n",
      "Epoch 681/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1933.4198 - root_mean_squared_error: 7478.1299 - val_loss: 2178.8416 - val_root_mean_squared_error: 10395.4248\n",
      "Epoch 682/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1926.7654 - root_mean_squared_error: 7468.4829 - val_loss: 2162.8982 - val_root_mean_squared_error: 10322.6338\n",
      "Epoch 683/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1938.4390 - root_mean_squared_error: 7466.3989 - val_loss: 2151.5701 - val_root_mean_squared_error: 10363.0586\n",
      "Epoch 684/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1927.6500 - root_mean_squared_error: 7470.2646 - val_loss: 2163.5383 - val_root_mean_squared_error: 10374.0928\n",
      "Epoch 685/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1927.4222 - root_mean_squared_error: 7493.7988 - val_loss: 2153.3684 - val_root_mean_squared_error: 10348.6709\n",
      "Epoch 686/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1947.8396 - root_mean_squared_error: 7495.7886 - val_loss: 2181.4573 - val_root_mean_squared_error: 10218.7568\n",
      "Epoch 687/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1929.3817 - root_mean_squared_error: 7485.1572 - val_loss: 2154.6719 - val_root_mean_squared_error: 10499.0918\n",
      "Epoch 688/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1946.9955 - root_mean_squared_error: 7496.6743 - val_loss: 2159.9507 - val_root_mean_squared_error: 10373.8906\n",
      "Epoch 689/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1929.0393 - root_mean_squared_error: 7469.4946 - val_loss: 2157.4690 - val_root_mean_squared_error: 10455.2256\n",
      "Epoch 690/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1929.7062 - root_mean_squared_error: 7462.5776 - val_loss: 2165.3550 - val_root_mean_squared_error: 10253.2109\n",
      "Epoch 691/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1947.5298 - root_mean_squared_error: 7490.4863 - val_loss: 2163.6973 - val_root_mean_squared_error: 10265.1279\n",
      "Epoch 692/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1956.2142 - root_mean_squared_error: 7515.3208 - val_loss: 2170.4336 - val_root_mean_squared_error: 10534.0947\n",
      "Epoch 693/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1948.4050 - root_mean_squared_error: 7459.2388 - val_loss: 2168.4438 - val_root_mean_squared_error: 10180.0781\n",
      "Epoch 694/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1943.8417 - root_mean_squared_error: 7460.8799 - val_loss: 2143.5430 - val_root_mean_squared_error: 10164.1543\n",
      "Epoch 695/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1939.5298 - root_mean_squared_error: 7469.3901 - val_loss: 2160.8145 - val_root_mean_squared_error: 10260.3350\n",
      "Epoch 696/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1934.9153 - root_mean_squared_error: 7414.6460 - val_loss: 2157.2908 - val_root_mean_squared_error: 10366.5078\n",
      "Epoch 697/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1934.2471 - root_mean_squared_error: 7484.0659 - val_loss: 2174.5129 - val_root_mean_squared_error: 10216.3447\n",
      "Epoch 698/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1941.1449 - root_mean_squared_error: 7469.6777 - val_loss: 2156.8896 - val_root_mean_squared_error: 10362.8545\n",
      "Epoch 699/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1927.0371 - root_mean_squared_error: 7473.3267 - val_loss: 2153.7136 - val_root_mean_squared_error: 10403.9707\n",
      "Epoch 700/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1928.4305 - root_mean_squared_error: 7484.0000 - val_loss: 2147.0671 - val_root_mean_squared_error: 10286.9307\n",
      "Epoch 701/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1936.8059 - root_mean_squared_error: 7452.4834 - val_loss: 2150.6189 - val_root_mean_squared_error: 10206.1025\n",
      "Epoch 702/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1946.6515 - root_mean_squared_error: 7519.6074 - val_loss: 2166.5979 - val_root_mean_squared_error: 10311.6650\n",
      "Epoch 703/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1939.2301 - root_mean_squared_error: 7489.8325 - val_loss: 2156.6875 - val_root_mean_squared_error: 10479.3291\n",
      "Epoch 704/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1953.0087 - root_mean_squared_error: 7426.9492 - val_loss: 2152.6328 - val_root_mean_squared_error: 10331.2197\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 705/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1923.4728 - root_mean_squared_error: 7401.0518 - val_loss: 2181.8091 - val_root_mean_squared_error: 10075.3701\n",
      "Epoch 706/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1959.1042 - root_mean_squared_error: 7445.2300 - val_loss: 2157.1011 - val_root_mean_squared_error: 10253.1152\n",
      "Epoch 707/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1958.8743 - root_mean_squared_error: 7479.4844 - val_loss: 2140.7876 - val_root_mean_squared_error: 10292.8750\n",
      "Epoch 708/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1935.3922 - root_mean_squared_error: 7481.3086 - val_loss: 2168.1833 - val_root_mean_squared_error: 10194.0273\n",
      "Epoch 709/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1935.7478 - root_mean_squared_error: 7526.6470 - val_loss: 2150.8433 - val_root_mean_squared_error: 10405.9414\n",
      "Epoch 710/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1936.2123 - root_mean_squared_error: 7477.3027 - val_loss: 2156.9924 - val_root_mean_squared_error: 10406.4346\n",
      "Epoch 711/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1948.7966 - root_mean_squared_error: 7474.3599 - val_loss: 2146.9470 - val_root_mean_squared_error: 10233.9150\n",
      "Epoch 712/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1943.0786 - root_mean_squared_error: 7538.0068 - val_loss: 2175.4509 - val_root_mean_squared_error: 10195.8867\n",
      "Epoch 713/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1942.4639 - root_mean_squared_error: 7491.5850 - val_loss: 2157.3987 - val_root_mean_squared_error: 10413.5205\n",
      "Epoch 714/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1925.8651 - root_mean_squared_error: 7459.5688 - val_loss: 2179.6577 - val_root_mean_squared_error: 10232.4746\n",
      "Epoch 715/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1933.1941 - root_mean_squared_error: 7496.2637 - val_loss: 2151.6909 - val_root_mean_squared_error: 10500.7139\n",
      "Epoch 716/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1926.4323 - root_mean_squared_error: 7493.0439 - val_loss: 2169.4321 - val_root_mean_squared_error: 10299.9229\n",
      "Epoch 717/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1953.0825 - root_mean_squared_error: 7458.2002 - val_loss: 2163.1531 - val_root_mean_squared_error: 10483.8262\n",
      "Epoch 718/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1942.1222 - root_mean_squared_error: 7469.8657 - val_loss: 2149.8738 - val_root_mean_squared_error: 10153.7012\n",
      "Epoch 719/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1923.6650 - root_mean_squared_error: 7431.8306 - val_loss: 2160.2546 - val_root_mean_squared_error: 10182.6025\n",
      "Epoch 720/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1925.9830 - root_mean_squared_error: 7441.0879 - val_loss: 2137.3989 - val_root_mean_squared_error: 10283.1250\n",
      "Epoch 721/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1932.0917 - root_mean_squared_error: 7502.7642 - val_loss: 2147.1685 - val_root_mean_squared_error: 10405.4219\n",
      "Epoch 722/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1922.7808 - root_mean_squared_error: 7490.8403 - val_loss: 2154.6509 - val_root_mean_squared_error: 10183.9941\n",
      "Epoch 723/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1925.9601 - root_mean_squared_error: 7434.8203 - val_loss: 2138.0994 - val_root_mean_squared_error: 10257.9209\n",
      "Epoch 724/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1922.3715 - root_mean_squared_error: 7446.7349 - val_loss: 2180.6572 - val_root_mean_squared_error: 10131.5713\n",
      "Epoch 725/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1941.5693 - root_mean_squared_error: 7459.2324 - val_loss: 2144.3618 - val_root_mean_squared_error: 10236.3174\n",
      "Epoch 726/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1939.4703 - root_mean_squared_error: 7481.6611 - val_loss: 2151.1211 - val_root_mean_squared_error: 10466.9277\n",
      "Epoch 727/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1924.4280 - root_mean_squared_error: 7432.4248 - val_loss: 2167.0596 - val_root_mean_squared_error: 10075.4365\n",
      "Epoch 728/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1938.1206 - root_mean_squared_error: 7437.7148 - val_loss: 2134.5952 - val_root_mean_squared_error: 10191.5674\n",
      "Epoch 729/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.0111 - root_mean_squared_error: 7451.4312 - val_loss: 2136.4041 - val_root_mean_squared_error: 10250.9756\n",
      "Epoch 730/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1934.2662 - root_mean_squared_error: 7458.3638 - val_loss: 2150.5339 - val_root_mean_squared_error: 10196.9990\n",
      "Epoch 731/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1919.6785 - root_mean_squared_error: 7451.3701 - val_loss: 2146.9351 - val_root_mean_squared_error: 10249.3965\n",
      "Epoch 732/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1933.8964 - root_mean_squared_error: 7479.6357 - val_loss: 2147.4700 - val_root_mean_squared_error: 10307.6807\n",
      "Epoch 733/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1923.2235 - root_mean_squared_error: 7461.8750 - val_loss: 2155.9609 - val_root_mean_squared_error: 10376.2910\n",
      "Epoch 734/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1926.5869 - root_mean_squared_error: 7452.3408 - val_loss: 2165.7815 - val_root_mean_squared_error: 10397.5928\n",
      "Epoch 735/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1931.4210 - root_mean_squared_error: 7526.8530 - val_loss: 2162.0989 - val_root_mean_squared_error: 10300.7920\n",
      "Epoch 736/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1927.5563 - root_mean_squared_error: 7493.7168 - val_loss: 2161.9211 - val_root_mean_squared_error: 10323.2920\n",
      "Epoch 737/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.3545 - root_mean_squared_error: 7460.0415 - val_loss: 2144.9922 - val_root_mean_squared_error: 10324.6230\n",
      "Epoch 738/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1930.0524 - root_mean_squared_error: 7451.2124 - val_loss: 2149.5081 - val_root_mean_squared_error: 10379.5420\n",
      "Epoch 739/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1942.2482 - root_mean_squared_error: 7496.8379 - val_loss: 2174.4092 - val_root_mean_squared_error: 10233.1582\n",
      "Epoch 740/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1924.3821 - root_mean_squared_error: 7476.4844 - val_loss: 2149.3701 - val_root_mean_squared_error: 10220.6406\n",
      "Epoch 741/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1922.9735 - root_mean_squared_error: 7434.3555 - val_loss: 2147.0168 - val_root_mean_squared_error: 10318.0020\n",
      "Epoch 742/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1919.1672 - root_mean_squared_error: 7444.0410 - val_loss: 2150.2961 - val_root_mean_squared_error: 10263.7861\n",
      "Epoch 743/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1923.5288 - root_mean_squared_error: 7453.8110 - val_loss: 2161.3081 - val_root_mean_squared_error: 10183.5410\n",
      "Epoch 744/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1924.5493 - root_mean_squared_error: 7441.2949 - val_loss: 2142.6890 - val_root_mean_squared_error: 10319.3750\n",
      "Epoch 745/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1922.7806 - root_mean_squared_error: 7426.8296 - val_loss: 2179.1121 - val_root_mean_squared_error: 10128.3525\n",
      "Epoch 746/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1935.4830 - root_mean_squared_error: 7446.1167 - val_loss: 2138.6350 - val_root_mean_squared_error: 10208.2002\n",
      "Epoch 747/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1930.2516 - root_mean_squared_error: 7415.6323 - val_loss: 2142.0508 - val_root_mean_squared_error: 10411.9297\n",
      "Epoch 748/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1948.4495 - root_mean_squared_error: 7429.6577 - val_loss: 2181.3708 - val_root_mean_squared_error: 10030.8789\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 749/2000\n",
      "10/10 [==============================] - 0s 16ms/step - loss: 1944.5841 - root_mean_squared_error: 7409.0010 - val_loss: 2139.4956 - val_root_mean_squared_error: 10135.8047\n",
      "Epoch 750/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1939.8309 - root_mean_squared_error: 7497.4658 - val_loss: 2140.3999 - val_root_mean_squared_error: 10269.3467\n",
      "Epoch 751/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1928.5150 - root_mean_squared_error: 7456.4683 - val_loss: 2150.0144 - val_root_mean_squared_error: 10330.7402\n",
      "Epoch 752/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1936.6829 - root_mean_squared_error: 7459.5708 - val_loss: 2146.4285 - val_root_mean_squared_error: 10421.6562\n",
      "Epoch 753/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1963.3989 - root_mean_squared_error: 7515.7734 - val_loss: 2144.9949 - val_root_mean_squared_error: 10171.5732\n",
      "Epoch 754/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1924.4281 - root_mean_squared_error: 7435.8506 - val_loss: 2130.9827 - val_root_mean_squared_error: 10225.1689\n",
      "Epoch 755/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1916.2679 - root_mean_squared_error: 7420.8301 - val_loss: 2161.3403 - val_root_mean_squared_error: 10118.6680\n",
      "Epoch 756/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1926.4495 - root_mean_squared_error: 7408.4458 - val_loss: 2137.0168 - val_root_mean_squared_error: 10270.0967\n",
      "Epoch 757/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1926.7280 - root_mean_squared_error: 7468.7485 - val_loss: 2152.4297 - val_root_mean_squared_error: 10220.2852\n",
      "Epoch 758/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1934.6960 - root_mean_squared_error: 7496.8364 - val_loss: 2157.3093 - val_root_mean_squared_error: 10313.2334\n",
      "Epoch 759/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1928.5188 - root_mean_squared_error: 7497.4834 - val_loss: 2146.4966 - val_root_mean_squared_error: 10188.0010\n",
      "Epoch 760/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1929.1011 - root_mean_squared_error: 7474.0435 - val_loss: 2133.9619 - val_root_mean_squared_error: 10252.9834\n",
      "Epoch 761/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1921.9630 - root_mean_squared_error: 7431.3877 - val_loss: 2137.8123 - val_root_mean_squared_error: 10321.5234\n",
      "Epoch 762/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1928.6973 - root_mean_squared_error: 7498.9668 - val_loss: 2155.7205 - val_root_mean_squared_error: 10047.3066\n",
      "Epoch 763/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1933.6864 - root_mean_squared_error: 7511.5757 - val_loss: 2146.3564 - val_root_mean_squared_error: 10157.6611\n",
      "Epoch 764/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1925.9739 - root_mean_squared_error: 7471.7861 - val_loss: 2130.7021 - val_root_mean_squared_error: 10311.0869\n",
      "Epoch 765/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1924.7698 - root_mean_squared_error: 7466.0210 - val_loss: 2149.4319 - val_root_mean_squared_error: 10228.3320\n",
      "Epoch 766/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1928.2539 - root_mean_squared_error: 7483.8550 - val_loss: 2154.9968 - val_root_mean_squared_error: 10297.1387\n",
      "Epoch 767/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1934.8920 - root_mean_squared_error: 7514.6143 - val_loss: 2166.1121 - val_root_mean_squared_error: 10231.1543\n",
      "Epoch 768/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1924.1534 - root_mean_squared_error: 7436.6016 - val_loss: 2127.0862 - val_root_mean_squared_error: 10189.4951\n",
      "Epoch 769/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.1285 - root_mean_squared_error: 7434.1738 - val_loss: 2139.3655 - val_root_mean_squared_error: 10187.0459\n",
      "Epoch 770/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1916.0719 - root_mean_squared_error: 7450.1797 - val_loss: 2140.5261 - val_root_mean_squared_error: 10298.7119\n",
      "Epoch 771/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1923.1560 - root_mean_squared_error: 7482.2344 - val_loss: 2160.6326 - val_root_mean_squared_error: 10165.2715\n",
      "Epoch 772/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1934.6998 - root_mean_squared_error: 7418.4019 - val_loss: 2152.6863 - val_root_mean_squared_error: 10213.9492\n",
      "Epoch 773/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.5375 - root_mean_squared_error: 7452.6309 - val_loss: 2133.7288 - val_root_mean_squared_error: 10332.3174\n",
      "Epoch 774/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1925.9878 - root_mean_squared_error: 7508.0361 - val_loss: 2148.5901 - val_root_mean_squared_error: 10197.3047\n",
      "Epoch 775/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1918.4866 - root_mean_squared_error: 7478.7510 - val_loss: 2151.2949 - val_root_mean_squared_error: 10177.8672\n",
      "Epoch 776/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1937.5095 - root_mean_squared_error: 7474.6221 - val_loss: 2141.4702 - val_root_mean_squared_error: 10235.2637\n",
      "Epoch 777/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1924.8353 - root_mean_squared_error: 7417.0713 - val_loss: 2146.1511 - val_root_mean_squared_error: 10315.5098\n",
      "Epoch 778/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1929.1615 - root_mean_squared_error: 7469.8315 - val_loss: 2141.6460 - val_root_mean_squared_error: 10298.5195\n",
      "Epoch 779/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1926.4226 - root_mean_squared_error: 7442.2393 - val_loss: 2146.4966 - val_root_mean_squared_error: 10232.8037\n",
      "Epoch 780/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1918.1123 - root_mean_squared_error: 7442.0669 - val_loss: 2141.6079 - val_root_mean_squared_error: 10146.0156\n",
      "Epoch 781/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1916.1716 - root_mean_squared_error: 7434.0527 - val_loss: 2146.4712 - val_root_mean_squared_error: 10225.0928\n",
      "Epoch 782/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1927.7622 - root_mean_squared_error: 7501.0791 - val_loss: 2182.9907 - val_root_mean_squared_error: 10152.4121\n",
      "Epoch 783/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1924.9115 - root_mean_squared_error: 7420.5034 - val_loss: 2144.9631 - val_root_mean_squared_error: 10247.3652\n",
      "Epoch 784/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.9155 - root_mean_squared_error: 7437.0361 - val_loss: 2137.8618 - val_root_mean_squared_error: 10194.1709\n",
      "Epoch 785/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1921.3438 - root_mean_squared_error: 7432.1924 - val_loss: 2129.8403 - val_root_mean_squared_error: 10353.6309\n",
      "Epoch 786/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1927.4755 - root_mean_squared_error: 7491.8950 - val_loss: 2144.0913 - val_root_mean_squared_error: 10368.9258\n",
      "Epoch 787/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1918.9607 - root_mean_squared_error: 7462.2119 - val_loss: 2196.2332 - val_root_mean_squared_error: 10086.1758\n",
      "Epoch 788/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.8683 - root_mean_squared_error: 7422.9429 - val_loss: 2141.8384 - val_root_mean_squared_error: 10268.6016\n",
      "Epoch 789/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1933.5245 - root_mean_squared_error: 7481.3188 - val_loss: 2134.7146 - val_root_mean_squared_error: 10346.4062\n",
      "Epoch 790/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1922.9501 - root_mean_squared_error: 7475.1982 - val_loss: 2145.0627 - val_root_mean_squared_error: 10224.9141\n",
      "Epoch 791/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1920.1179 - root_mean_squared_error: 7426.0396 - val_loss: 2125.7720 - val_root_mean_squared_error: 10215.4092\n",
      "Epoch 792/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1924.6847 - root_mean_squared_error: 7488.8076 - val_loss: 2129.7607 - val_root_mean_squared_error: 10216.5547\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 793/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1927.4546 - root_mean_squared_error: 7447.7896 - val_loss: 2162.9028 - val_root_mean_squared_error: 10071.0000\n",
      "Epoch 794/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1940.8914 - root_mean_squared_error: 7500.2422 - val_loss: 2129.8564 - val_root_mean_squared_error: 10228.6621\n",
      "Epoch 795/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1922.5164 - root_mean_squared_error: 7442.7661 - val_loss: 2136.4995 - val_root_mean_squared_error: 10281.2051\n",
      "Epoch 796/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1927.3776 - root_mean_squared_error: 7477.5469 - val_loss: 2142.0134 - val_root_mean_squared_error: 10063.5684\n",
      "Epoch 797/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1923.2012 - root_mean_squared_error: 7443.4009 - val_loss: 2122.7649 - val_root_mean_squared_error: 10266.4082\n",
      "Epoch 798/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1914.3442 - root_mean_squared_error: 7464.1455 - val_loss: 2149.3440 - val_root_mean_squared_error: 10236.5293\n",
      "Epoch 799/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1914.6455 - root_mean_squared_error: 7472.5625 - val_loss: 2150.2114 - val_root_mean_squared_error: 10098.6182\n",
      "Epoch 800/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1925.5332 - root_mean_squared_error: 7422.1182 - val_loss: 2138.9883 - val_root_mean_squared_error: 10226.5850\n",
      "Epoch 801/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1926.9005 - root_mean_squared_error: 7438.5527 - val_loss: 2172.4072 - val_root_mean_squared_error: 10072.6562\n",
      "Epoch 802/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1927.9447 - root_mean_squared_error: 7447.7812 - val_loss: 2125.9465 - val_root_mean_squared_error: 10243.8848\n",
      "Epoch 803/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.3639 - root_mean_squared_error: 7474.2832 - val_loss: 2132.2268 - val_root_mean_squared_error: 10262.9922\n",
      "Epoch 804/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1918.3066 - root_mean_squared_error: 7438.3726 - val_loss: 2136.0190 - val_root_mean_squared_error: 10193.5918\n",
      "Epoch 805/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1918.5658 - root_mean_squared_error: 7437.7944 - val_loss: 2130.1873 - val_root_mean_squared_error: 10164.2549\n",
      "Epoch 806/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1929.6672 - root_mean_squared_error: 7533.8643 - val_loss: 2167.1106 - val_root_mean_squared_error: 10235.6865\n",
      "Epoch 807/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1940.5508 - root_mean_squared_error: 7528.1353 - val_loss: 2152.5542 - val_root_mean_squared_error: 10484.6611\n",
      "Epoch 808/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1925.7407 - root_mean_squared_error: 7395.0405 - val_loss: 2147.3833 - val_root_mean_squared_error: 10152.6475\n",
      "Epoch 809/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1929.5870 - root_mean_squared_error: 7485.9116 - val_loss: 2148.0471 - val_root_mean_squared_error: 10072.9551\n",
      "Epoch 810/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1916.0815 - root_mean_squared_error: 7396.8677 - val_loss: 2124.5703 - val_root_mean_squared_error: 10252.4639\n",
      "Epoch 811/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.2158 - root_mean_squared_error: 7475.1279 - val_loss: 2131.6829 - val_root_mean_squared_error: 10214.9189\n",
      "Epoch 812/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1917.3318 - root_mean_squared_error: 7477.5552 - val_loss: 2167.7917 - val_root_mean_squared_error: 10106.8271\n",
      "Epoch 813/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1925.6791 - root_mean_squared_error: 7420.1851 - val_loss: 2166.8931 - val_root_mean_squared_error: 10300.0605\n",
      "Epoch 814/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1943.8453 - root_mean_squared_error: 7445.0083 - val_loss: 2140.3840 - val_root_mean_squared_error: 9990.2695\n",
      "Epoch 815/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1933.0505 - root_mean_squared_error: 7435.8281 - val_loss: 2125.7051 - val_root_mean_squared_error: 10019.1748\n",
      "Epoch 816/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1918.3209 - root_mean_squared_error: 7406.5854 - val_loss: 2131.8352 - val_root_mean_squared_error: 10123.9990\n",
      "Epoch 817/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1920.9609 - root_mean_squared_error: 7479.8535 - val_loss: 2151.2881 - val_root_mean_squared_error: 10051.0654\n",
      "Epoch 818/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1928.5787 - root_mean_squared_error: 7419.6958 - val_loss: 2126.4978 - val_root_mean_squared_error: 10047.9473\n",
      "Epoch 819/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1923.5962 - root_mean_squared_error: 7464.8696 - val_loss: 2118.9468 - val_root_mean_squared_error: 10151.7861\n",
      "Epoch 820/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1919.1714 - root_mean_squared_error: 7423.8042 - val_loss: 2130.4341 - val_root_mean_squared_error: 10139.3809\n",
      "Epoch 821/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1942.3977 - root_mean_squared_error: 7453.8447 - val_loss: 2187.1914 - val_root_mean_squared_error: 9978.4551\n",
      "Epoch 822/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1949.1823 - root_mean_squared_error: 7385.3242 - val_loss: 2152.3220 - val_root_mean_squared_error: 10297.4219\n",
      "Epoch 823/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1935.6785 - root_mean_squared_error: 7412.2612 - val_loss: 2138.3345 - val_root_mean_squared_error: 10081.0176\n",
      "Epoch 824/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1912.0209 - root_mean_squared_error: 7424.3188 - val_loss: 2131.1580 - val_root_mean_squared_error: 10186.8672\n",
      "Epoch 825/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.8910 - root_mean_squared_error: 7434.6084 - val_loss: 2132.9861 - val_root_mean_squared_error: 10161.1396\n",
      "Epoch 826/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1911.5499 - root_mean_squared_error: 7425.6880 - val_loss: 2152.4333 - val_root_mean_squared_error: 10050.5742\n",
      "Epoch 827/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1922.3711 - root_mean_squared_error: 7392.1099 - val_loss: 2133.3674 - val_root_mean_squared_error: 10249.0928\n",
      "Epoch 828/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1944.7532 - root_mean_squared_error: 7459.8208 - val_loss: 2147.1741 - val_root_mean_squared_error: 10122.4736\n",
      "Epoch 829/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1913.9092 - root_mean_squared_error: 7423.8716 - val_loss: 2127.7307 - val_root_mean_squared_error: 10224.0996\n",
      "Epoch 830/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1937.0435 - root_mean_squared_error: 7460.7222 - val_loss: 2112.4973 - val_root_mean_squared_error: 10131.2363\n",
      "Epoch 831/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1919.0715 - root_mean_squared_error: 7444.9219 - val_loss: 2137.1328 - val_root_mean_squared_error: 10085.1514\n",
      "Epoch 832/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1930.1429 - root_mean_squared_error: 7458.6357 - val_loss: 2130.5393 - val_root_mean_squared_error: 10153.5146\n",
      "Epoch 833/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1925.0231 - root_mean_squared_error: 7442.2314 - val_loss: 2128.6208 - val_root_mean_squared_error: 10429.4199\n",
      "Epoch 834/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1921.8395 - root_mean_squared_error: 7457.8682 - val_loss: 2164.4656 - val_root_mean_squared_error: 10081.9717\n",
      "Epoch 835/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1921.9639 - root_mean_squared_error: 7416.0347 - val_loss: 2129.7769 - val_root_mean_squared_error: 10133.0977\n",
      "Epoch 836/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1925.4597 - root_mean_squared_error: 7442.8247 - val_loss: 2130.8962 - val_root_mean_squared_error: 10171.3506\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 837/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.0170 - root_mean_squared_error: 7444.0918 - val_loss: 2139.6672 - val_root_mean_squared_error: 10015.4385\n",
      "Epoch 838/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1922.0610 - root_mean_squared_error: 7436.1387 - val_loss: 2118.4834 - val_root_mean_squared_error: 10156.0566\n",
      "Epoch 839/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.2605 - root_mean_squared_error: 7444.1753 - val_loss: 2137.3086 - val_root_mean_squared_error: 10120.5420\n",
      "Epoch 840/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1912.4956 - root_mean_squared_error: 7428.1064 - val_loss: 2124.8901 - val_root_mean_squared_error: 10250.5068\n",
      "Epoch 841/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1915.8444 - root_mean_squared_error: 7461.4854 - val_loss: 2163.7817 - val_root_mean_squared_error: 10096.3555\n",
      "Epoch 842/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1918.8866 - root_mean_squared_error: 7441.3560 - val_loss: 2148.8523 - val_root_mean_squared_error: 10325.4219\n",
      "Epoch 843/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1924.0674 - root_mean_squared_error: 7525.5620 - val_loss: 2141.8406 - val_root_mean_squared_error: 10009.7520\n",
      "Epoch 844/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1918.7723 - root_mean_squared_error: 7416.4043 - val_loss: 2130.7874 - val_root_mean_squared_error: 10135.9375\n",
      "Epoch 845/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1917.0928 - root_mean_squared_error: 7448.7109 - val_loss: 2145.2883 - val_root_mean_squared_error: 10183.9238\n",
      "Epoch 846/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1922.9961 - root_mean_squared_error: 7440.4136 - val_loss: 2132.4456 - val_root_mean_squared_error: 10225.8115\n",
      "Epoch 847/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1931.2637 - root_mean_squared_error: 7432.5586 - val_loss: 2129.4158 - val_root_mean_squared_error: 9872.0781\n",
      "Epoch 848/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1938.9738 - root_mean_squared_error: 7380.6758 - val_loss: 2109.8250 - val_root_mean_squared_error: 9945.7275\n",
      "Epoch 849/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1923.9530 - root_mean_squared_error: 7416.0146 - val_loss: 2106.6790 - val_root_mean_squared_error: 10193.0361\n",
      "Epoch 850/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1921.4445 - root_mean_squared_error: 7426.5742 - val_loss: 2126.7234 - val_root_mean_squared_error: 10094.0127\n",
      "Epoch 851/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1924.4344 - root_mean_squared_error: 7466.3071 - val_loss: 2145.8884 - val_root_mean_squared_error: 10000.1729\n",
      "Epoch 852/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1937.4565 - root_mean_squared_error: 7365.9683 - val_loss: 2127.0708 - val_root_mean_squared_error: 10104.6016\n",
      "Epoch 853/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1944.9919 - root_mean_squared_error: 7374.7065 - val_loss: 2126.6194 - val_root_mean_squared_error: 10195.8965\n",
      "Epoch 854/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1934.2318 - root_mean_squared_error: 7411.5156 - val_loss: 2136.2422 - val_root_mean_squared_error: 9968.3018\n",
      "Epoch 855/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1927.7854 - root_mean_squared_error: 7452.8984 - val_loss: 2135.5166 - val_root_mean_squared_error: 9992.2822\n",
      "Epoch 856/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1943.9524 - root_mean_squared_error: 7384.3701 - val_loss: 2127.1731 - val_root_mean_squared_error: 10287.6699\n",
      "Epoch 857/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1943.7378 - root_mean_squared_error: 7424.4800 - val_loss: 2120.3279 - val_root_mean_squared_error: 10093.6504\n",
      "Epoch 858/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1948.1884 - root_mean_squared_error: 7483.2896 - val_loss: 2142.8320 - val_root_mean_squared_error: 9910.3018\n",
      "Epoch 859/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1932.4850 - root_mean_squared_error: 7366.7803 - val_loss: 2121.4319 - val_root_mean_squared_error: 10132.0908\n",
      "Epoch 860/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1925.1805 - root_mean_squared_error: 7444.7422 - val_loss: 2144.3167 - val_root_mean_squared_error: 10008.0078\n",
      "Epoch 861/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1926.2347 - root_mean_squared_error: 7485.7021 - val_loss: 2154.7358 - val_root_mean_squared_error: 9925.7051\n",
      "Epoch 862/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1949.6935 - root_mean_squared_error: 7415.2646 - val_loss: 2135.5076 - val_root_mean_squared_error: 10266.0107\n",
      "Epoch 863/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 2001.4310 - root_mean_squared_error: 7464.3579 - val_loss: 2178.9348 - val_root_mean_squared_error: 9733.9775\n",
      "Epoch 864/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1937.8878 - root_mean_squared_error: 7414.2544 - val_loss: 2137.8547 - val_root_mean_squared_error: 10216.2383\n",
      "Epoch 865/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1927.9460 - root_mean_squared_error: 7460.6118 - val_loss: 2131.9851 - val_root_mean_squared_error: 10129.5947\n",
      "Epoch 866/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1929.8329 - root_mean_squared_error: 7410.6309 - val_loss: 2147.5710 - val_root_mean_squared_error: 10205.9668\n",
      "Epoch 867/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1940.3763 - root_mean_squared_error: 7448.7227 - val_loss: 2155.1089 - val_root_mean_squared_error: 10035.1436\n",
      "Epoch 868/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1918.5560 - root_mean_squared_error: 7423.9067 - val_loss: 2132.5681 - val_root_mean_squared_error: 10112.9355\n",
      "Epoch 869/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1913.4847 - root_mean_squared_error: 7443.1138 - val_loss: 2115.0225 - val_root_mean_squared_error: 10181.7178\n",
      "Epoch 870/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1926.4233 - root_mean_squared_error: 7458.3198 - val_loss: 2158.7534 - val_root_mean_squared_error: 9915.2344\n",
      "Epoch 871/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1905.4117 - root_mean_squared_error: 7386.4902 - val_loss: 2119.7764 - val_root_mean_squared_error: 10172.8418\n",
      "Epoch 872/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1915.2346 - root_mean_squared_error: 7391.3071 - val_loss: 2128.9749 - val_root_mean_squared_error: 9924.9775\n",
      "Epoch 873/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1923.6940 - root_mean_squared_error: 7429.3438 - val_loss: 2108.9038 - val_root_mean_squared_error: 10013.3877\n",
      "Epoch 874/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1934.4526 - root_mean_squared_error: 7421.3711 - val_loss: 2128.9255 - val_root_mean_squared_error: 10202.6064\n",
      "Epoch 875/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1932.7938 - root_mean_squared_error: 7469.9863 - val_loss: 2125.5684 - val_root_mean_squared_error: 10034.7227\n",
      "Epoch 876/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1926.5573 - root_mean_squared_error: 7437.7510 - val_loss: 2138.2297 - val_root_mean_squared_error: 10192.3086\n",
      "Epoch 877/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1914.1774 - root_mean_squared_error: 7417.5088 - val_loss: 2130.9414 - val_root_mean_squared_error: 10105.9150\n",
      "Epoch 878/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1912.1783 - root_mean_squared_error: 7437.1758 - val_loss: 2111.1062 - val_root_mean_squared_error: 9974.9160\n",
      "Epoch 879/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1914.7826 - root_mean_squared_error: 7430.2715 - val_loss: 2093.1790 - val_root_mean_squared_error: 10011.2764\n",
      "Epoch 880/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1921.4388 - root_mean_squared_error: 7430.3906 - val_loss: 2122.1597 - val_root_mean_squared_error: 9884.3604\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 881/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1912.0693 - root_mean_squared_error: 7411.4097 - val_loss: 2116.6860 - val_root_mean_squared_error: 10064.2656\n",
      "Epoch 882/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1913.4009 - root_mean_squared_error: 7466.4883 - val_loss: 2119.1562 - val_root_mean_squared_error: 10199.0469\n",
      "Epoch 883/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1904.0620 - root_mean_squared_error: 7442.8716 - val_loss: 2144.9700 - val_root_mean_squared_error: 10049.7705\n",
      "Epoch 884/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1910.5968 - root_mean_squared_error: 7429.3867 - val_loss: 2117.8828 - val_root_mean_squared_error: 10085.8926\n",
      "Epoch 885/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1913.1500 - root_mean_squared_error: 7439.4160 - val_loss: 2143.1360 - val_root_mean_squared_error: 10019.4619\n",
      "Epoch 886/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1922.4578 - root_mean_squared_error: 7385.1528 - val_loss: 2124.5054 - val_root_mean_squared_error: 10223.3408\n",
      "Epoch 887/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1915.3340 - root_mean_squared_error: 7427.2954 - val_loss: 2122.6550 - val_root_mean_squared_error: 10040.3359\n",
      "Epoch 888/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1905.4590 - root_mean_squared_error: 7423.0786 - val_loss: 2104.7019 - val_root_mean_squared_error: 10122.7852\n",
      "Epoch 889/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1919.7753 - root_mean_squared_error: 7420.3037 - val_loss: 2119.2087 - val_root_mean_squared_error: 10205.0527\n",
      "Epoch 890/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1912.0198 - root_mean_squared_error: 7411.7354 - val_loss: 2129.1641 - val_root_mean_squared_error: 9979.0430\n",
      "Epoch 891/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1905.5560 - root_mean_squared_error: 7434.2964 - val_loss: 2103.1743 - val_root_mean_squared_error: 10151.7559\n",
      "Epoch 892/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1908.3260 - root_mean_squared_error: 7434.5532 - val_loss: 2107.3657 - val_root_mean_squared_error: 10128.2734\n",
      "Epoch 893/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1915.1400 - root_mean_squared_error: 7474.4199 - val_loss: 2128.7734 - val_root_mean_squared_error: 10109.5156\n",
      "Epoch 894/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.4617 - root_mean_squared_error: 7450.3076 - val_loss: 2131.5588 - val_root_mean_squared_error: 10161.3594\n",
      "Epoch 895/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1905.5345 - root_mean_squared_error: 7428.2500 - val_loss: 2125.1868 - val_root_mean_squared_error: 10037.1240\n",
      "Epoch 896/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1909.1678 - root_mean_squared_error: 7443.5737 - val_loss: 2111.2327 - val_root_mean_squared_error: 10044.5928\n",
      "Epoch 897/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1911.5709 - root_mean_squared_error: 7412.9214 - val_loss: 2117.8560 - val_root_mean_squared_error: 9964.8857\n",
      "Epoch 898/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1914.8768 - root_mean_squared_error: 7389.0811 - val_loss: 2113.0955 - val_root_mean_squared_error: 10156.4160\n",
      "Epoch 899/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1930.1493 - root_mean_squared_error: 7458.9561 - val_loss: 2121.3679 - val_root_mean_squared_error: 10372.1953\n",
      "Epoch 900/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1919.7756 - root_mean_squared_error: 7472.6904 - val_loss: 2127.0229 - val_root_mean_squared_error: 10180.2051\n",
      "Epoch 901/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1928.1862 - root_mean_squared_error: 7440.5361 - val_loss: 2131.9614 - val_root_mean_squared_error: 10153.4453\n",
      "Epoch 902/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1928.6299 - root_mean_squared_error: 7407.1323 - val_loss: 2113.5662 - val_root_mean_squared_error: 10155.2861\n",
      "Epoch 903/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1935.8981 - root_mean_squared_error: 7508.4609 - val_loss: 2131.3611 - val_root_mean_squared_error: 9986.3828\n",
      "Epoch 904/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.5375 - root_mean_squared_error: 7461.1870 - val_loss: 2117.7673 - val_root_mean_squared_error: 10129.8379\n",
      "Epoch 905/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1908.9492 - root_mean_squared_error: 7435.1533 - val_loss: 2116.0376 - val_root_mean_squared_error: 10177.8633\n",
      "Epoch 906/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1910.0901 - root_mean_squared_error: 7416.0459 - val_loss: 2101.3442 - val_root_mean_squared_error: 10093.4961\n",
      "Epoch 907/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1921.4208 - root_mean_squared_error: 7398.8164 - val_loss: 2107.6143 - val_root_mean_squared_error: 9956.0674\n",
      "Epoch 908/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1905.6459 - root_mean_squared_error: 7436.4194 - val_loss: 2115.0117 - val_root_mean_squared_error: 10095.4990\n",
      "Epoch 909/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1904.2311 - root_mean_squared_error: 7428.9077 - val_loss: 2122.6997 - val_root_mean_squared_error: 10043.1611\n",
      "Epoch 910/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1918.0183 - root_mean_squared_error: 7434.2603 - val_loss: 2098.7888 - val_root_mean_squared_error: 10114.4824\n",
      "Epoch 911/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1937.7784 - root_mean_squared_error: 7415.0684 - val_loss: 2126.8359 - val_root_mean_squared_error: 10084.4473\n",
      "Epoch 912/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1955.3094 - root_mean_squared_error: 7433.4629 - val_loss: 2135.0825 - val_root_mean_squared_error: 9991.2344\n",
      "Epoch 913/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1936.9625 - root_mean_squared_error: 7471.5132 - val_loss: 2103.3057 - val_root_mean_squared_error: 10354.8408\n",
      "Epoch 914/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1914.5116 - root_mean_squared_error: 7478.3032 - val_loss: 2156.5996 - val_root_mean_squared_error: 9949.5518\n",
      "Epoch 915/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.3766 - root_mean_squared_error: 7453.8135 - val_loss: 2118.3447 - val_root_mean_squared_error: 10149.8701\n",
      "Epoch 916/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1912.0691 - root_mean_squared_error: 7398.7876 - val_loss: 2110.5859 - val_root_mean_squared_error: 10139.9111\n",
      "Epoch 917/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1923.3552 - root_mean_squared_error: 7528.5015 - val_loss: 2158.4900 - val_root_mean_squared_error: 9808.4873\n",
      "Epoch 918/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1933.0726 - root_mean_squared_error: 7465.5391 - val_loss: 2111.6843 - val_root_mean_squared_error: 10165.5664\n",
      "Epoch 919/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1911.6722 - root_mean_squared_error: 7435.5322 - val_loss: 2112.3967 - val_root_mean_squared_error: 10051.3193\n",
      "Epoch 920/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1912.1614 - root_mean_squared_error: 7432.8379 - val_loss: 2118.0288 - val_root_mean_squared_error: 10087.7520\n",
      "Epoch 921/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1904.2117 - root_mean_squared_error: 7431.9355 - val_loss: 2107.0222 - val_root_mean_squared_error: 10097.7842\n",
      "Epoch 922/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1902.8577 - root_mean_squared_error: 7372.3335 - val_loss: 2110.6699 - val_root_mean_squared_error: 9736.8281\n",
      "Epoch 923/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1921.7679 - root_mean_squared_error: 7437.0874 - val_loss: 2086.2119 - val_root_mean_squared_error: 9881.6826\n",
      "Epoch 924/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1920.2413 - root_mean_squared_error: 7392.6387 - val_loss: 2104.8416 - val_root_mean_squared_error: 9929.8936\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 925/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1917.6503 - root_mean_squared_error: 7392.2842 - val_loss: 2094.3826 - val_root_mean_squared_error: 10011.5439\n",
      "Epoch 926/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1921.0958 - root_mean_squared_error: 7479.0059 - val_loss: 2100.3887 - val_root_mean_squared_error: 10213.8359\n",
      "Epoch 927/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1929.0458 - root_mean_squared_error: 7406.9282 - val_loss: 2111.3926 - val_root_mean_squared_error: 9897.4092\n",
      "Epoch 928/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1910.5486 - root_mean_squared_error: 7382.8481 - val_loss: 2107.4846 - val_root_mean_squared_error: 9920.6826\n",
      "Epoch 929/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.8162 - root_mean_squared_error: 7438.2583 - val_loss: 2088.0168 - val_root_mean_squared_error: 9977.7422\n",
      "Epoch 930/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1910.0093 - root_mean_squared_error: 7438.1650 - val_loss: 2120.9836 - val_root_mean_squared_error: 10056.1924\n",
      "Epoch 931/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.7338 - root_mean_squared_error: 7487.9434 - val_loss: 2110.9617 - val_root_mean_squared_error: 10244.7051\n",
      "Epoch 932/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1914.9639 - root_mean_squared_error: 7455.2324 - val_loss: 2107.5015 - val_root_mean_squared_error: 10121.3398\n",
      "Epoch 933/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1906.8644 - root_mean_squared_error: 7398.0781 - val_loss: 2115.0420 - val_root_mean_squared_error: 9983.0645\n",
      "Epoch 934/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1904.4249 - root_mean_squared_error: 7432.6128 - val_loss: 2103.8845 - val_root_mean_squared_error: 10073.1621\n",
      "Epoch 935/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1898.3219 - root_mean_squared_error: 7421.4277 - val_loss: 2099.9363 - val_root_mean_squared_error: 10049.7305\n",
      "Epoch 936/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1914.1560 - root_mean_squared_error: 7459.7671 - val_loss: 2140.9111 - val_root_mean_squared_error: 10018.4609\n",
      "Epoch 937/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1928.7139 - root_mean_squared_error: 7473.8882 - val_loss: 2127.4019 - val_root_mean_squared_error: 9967.9287\n",
      "Epoch 938/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1914.9303 - root_mean_squared_error: 7418.5420 - val_loss: 2105.5215 - val_root_mean_squared_error: 9953.5459\n",
      "Epoch 939/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1903.3213 - root_mean_squared_error: 7422.6030 - val_loss: 2103.4409 - val_root_mean_squared_error: 10087.2988\n",
      "Epoch 940/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1924.4611 - root_mean_squared_error: 7461.9819 - val_loss: 2128.7886 - val_root_mean_squared_error: 9843.0391\n",
      "Epoch 941/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1921.9750 - root_mean_squared_error: 7420.9126 - val_loss: 2099.9980 - val_root_mean_squared_error: 9914.4668\n",
      "Epoch 942/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1915.1541 - root_mean_squared_error: 7422.3306 - val_loss: 2101.4089 - val_root_mean_squared_error: 10069.6758\n",
      "Epoch 943/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1932.4885 - root_mean_squared_error: 7440.9727 - val_loss: 2104.4285 - val_root_mean_squared_error: 10085.5205\n",
      "Epoch 944/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.0431 - root_mean_squared_error: 7405.7168 - val_loss: 2113.2178 - val_root_mean_squared_error: 9898.6689\n",
      "Epoch 945/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1916.9796 - root_mean_squared_error: 7427.7031 - val_loss: 2096.7395 - val_root_mean_squared_error: 10058.9834\n",
      "Epoch 946/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1917.3519 - root_mean_squared_error: 7436.1973 - val_loss: 2096.7935 - val_root_mean_squared_error: 10200.9385\n",
      "Epoch 947/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1933.8586 - root_mean_squared_error: 7430.1055 - val_loss: 2134.9463 - val_root_mean_squared_error: 9963.6367\n",
      "Epoch 948/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1906.2926 - root_mean_squared_error: 7441.4258 - val_loss: 2105.5833 - val_root_mean_squared_error: 10036.6602\n",
      "Epoch 949/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1905.5272 - root_mean_squared_error: 7430.5503 - val_loss: 2100.0105 - val_root_mean_squared_error: 9917.2148\n",
      "Epoch 950/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1901.7405 - root_mean_squared_error: 7430.9863 - val_loss: 2110.8582 - val_root_mean_squared_error: 9915.7676\n",
      "Epoch 951/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1913.3130 - root_mean_squared_error: 7358.3506 - val_loss: 2105.6147 - val_root_mean_squared_error: 10020.9590\n",
      "Epoch 952/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1916.0250 - root_mean_squared_error: 7404.0874 - val_loss: 2101.1172 - val_root_mean_squared_error: 9957.8613\n",
      "Epoch 953/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1902.8262 - root_mean_squared_error: 7390.4077 - val_loss: 2147.7754 - val_root_mean_squared_error: 9753.8984\n",
      "Epoch 954/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1940.4246 - root_mean_squared_error: 7353.5430 - val_loss: 2102.5278 - val_root_mean_squared_error: 9955.2061\n",
      "Epoch 955/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1922.3319 - root_mean_squared_error: 7422.3525 - val_loss: 2104.8074 - val_root_mean_squared_error: 9809.6846\n",
      "Epoch 956/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1918.8235 - root_mean_squared_error: 7354.9990 - val_loss: 2114.5347 - val_root_mean_squared_error: 10028.8848\n",
      "Epoch 957/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1920.1211 - root_mean_squared_error: 7432.8496 - val_loss: 2094.9075 - val_root_mean_squared_error: 10110.4268\n",
      "Epoch 958/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.4751 - root_mean_squared_error: 7419.8164 - val_loss: 2114.6650 - val_root_mean_squared_error: 9970.6406\n",
      "Epoch 959/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1904.0359 - root_mean_squared_error: 7425.0708 - val_loss: 2101.8137 - val_root_mean_squared_error: 10069.9756\n",
      "Epoch 960/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1911.5317 - root_mean_squared_error: 7415.5718 - val_loss: 2098.7292 - val_root_mean_squared_error: 10046.6660\n",
      "Epoch 961/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1902.2384 - root_mean_squared_error: 7397.6797 - val_loss: 2133.2065 - val_root_mean_squared_error: 9743.6221\n",
      "Epoch 962/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1948.6252 - root_mean_squared_error: 7424.8447 - val_loss: 2085.0703 - val_root_mean_squared_error: 9922.8018\n",
      "Epoch 963/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1911.3810 - root_mean_squared_error: 7382.4209 - val_loss: 2088.3958 - val_root_mean_squared_error: 9974.5039\n",
      "Epoch 964/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1906.5282 - root_mean_squared_error: 7413.0010 - val_loss: 2101.0044 - val_root_mean_squared_error: 9960.7607\n",
      "Epoch 965/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1900.0364 - root_mean_squared_error: 7411.7549 - val_loss: 2098.7556 - val_root_mean_squared_error: 9992.2979\n",
      "Epoch 966/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1904.9860 - root_mean_squared_error: 7486.3496 - val_loss: 2099.6199 - val_root_mean_squared_error: 10169.0098\n",
      "Epoch 967/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1907.9933 - root_mean_squared_error: 7474.1567 - val_loss: 2106.0613 - val_root_mean_squared_error: 10013.9238\n",
      "Epoch 968/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1902.5450 - root_mean_squared_error: 7397.7769 - val_loss: 2100.9883 - val_root_mean_squared_error: 9919.8115\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 969/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1897.6836 - root_mean_squared_error: 7401.8906 - val_loss: 2082.2341 - val_root_mean_squared_error: 10026.5293\n",
      "Epoch 970/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1902.3091 - root_mean_squared_error: 7429.4609 - val_loss: 2096.4517 - val_root_mean_squared_error: 10042.1543\n",
      "Epoch 971/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1921.3938 - root_mean_squared_error: 7406.8618 - val_loss: 2131.1082 - val_root_mean_squared_error: 9837.9883\n",
      "Epoch 972/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1923.1433 - root_mean_squared_error: 7386.3047 - val_loss: 2088.6104 - val_root_mean_squared_error: 9915.0928\n",
      "Epoch 973/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.5345 - root_mean_squared_error: 7331.9751 - val_loss: 2114.6685 - val_root_mean_squared_error: 10067.7432\n",
      "Epoch 974/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1946.9393 - root_mean_squared_error: 7489.4878 - val_loss: 2148.8042 - val_root_mean_squared_error: 9646.5898\n",
      "Epoch 975/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1896.0063 - root_mean_squared_error: 7338.1304 - val_loss: 2086.2332 - val_root_mean_squared_error: 10051.7529\n",
      "Epoch 976/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1913.9581 - root_mean_squared_error: 7404.6631 - val_loss: 2089.3352 - val_root_mean_squared_error: 9904.1025\n",
      "Epoch 977/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1906.4962 - root_mean_squared_error: 7393.0952 - val_loss: 2105.0708 - val_root_mean_squared_error: 9979.7891\n",
      "Epoch 978/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1903.2974 - root_mean_squared_error: 7421.1865 - val_loss: 2091.2146 - val_root_mean_squared_error: 9994.6006\n",
      "Epoch 979/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1914.2362 - root_mean_squared_error: 7441.4287 - val_loss: 2113.0835 - val_root_mean_squared_error: 9824.3574\n",
      "Epoch 980/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1898.9891 - root_mean_squared_error: 7413.9272 - val_loss: 2102.7939 - val_root_mean_squared_error: 9909.9395\n",
      "Epoch 981/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1903.0168 - root_mean_squared_error: 7412.0547 - val_loss: 2097.9563 - val_root_mean_squared_error: 10199.5020\n",
      "Epoch 982/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.2074 - root_mean_squared_error: 7435.2900 - val_loss: 2122.5369 - val_root_mean_squared_error: 9971.4180\n",
      "Epoch 983/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1903.0760 - root_mean_squared_error: 7380.4722 - val_loss: 2105.4343 - val_root_mean_squared_error: 9766.9424\n",
      "Epoch 984/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1907.8258 - root_mean_squared_error: 7365.4878 - val_loss: 2071.8955 - val_root_mean_squared_error: 9848.9062\n",
      "Epoch 985/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1905.4261 - root_mean_squared_error: 7382.7314 - val_loss: 2105.4666 - val_root_mean_squared_error: 9690.1846\n",
      "Epoch 986/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1905.1576 - root_mean_squared_error: 7453.6743 - val_loss: 2098.4019 - val_root_mean_squared_error: 10067.3242\n",
      "Epoch 987/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1908.3649 - root_mean_squared_error: 7383.1738 - val_loss: 2114.1057 - val_root_mean_squared_error: 9825.0146\n",
      "Epoch 988/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1917.4341 - root_mean_squared_error: 7350.3755 - val_loss: 2091.0300 - val_root_mean_squared_error: 9741.6094\n",
      "Epoch 989/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1917.1956 - root_mean_squared_error: 7336.9229 - val_loss: 2096.8799 - val_root_mean_squared_error: 10007.2861\n",
      "Epoch 990/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1921.4265 - root_mean_squared_error: 7418.9897 - val_loss: 2089.1658 - val_root_mean_squared_error: 9780.6875\n",
      "Epoch 991/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1899.7670 - root_mean_squared_error: 7378.1382 - val_loss: 2087.3057 - val_root_mean_squared_error: 9812.7705\n",
      "Epoch 992/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1899.4719 - root_mean_squared_error: 7391.9761 - val_loss: 2075.1421 - val_root_mean_squared_error: 9872.3975\n",
      "Epoch 993/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1902.0697 - root_mean_squared_error: 7447.6948 - val_loss: 2087.8206 - val_root_mean_squared_error: 9995.0898\n",
      "Epoch 994/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1902.8331 - root_mean_squared_error: 7433.2231 - val_loss: 2109.1201 - val_root_mean_squared_error: 9809.7930\n",
      "Epoch 995/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1927.4429 - root_mean_squared_error: 7368.1108 - val_loss: 2101.6309 - val_root_mean_squared_error: 9970.3906\n",
      "Epoch 996/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.1298 - root_mean_squared_error: 7400.7231 - val_loss: 2091.5928 - val_root_mean_squared_error: 9821.8721\n",
      "Epoch 997/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1907.3097 - root_mean_squared_error: 7352.0991 - val_loss: 2109.2998 - val_root_mean_squared_error: 9882.5928\n",
      "Epoch 998/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1931.3287 - root_mean_squared_error: 7433.2544 - val_loss: 2099.3687 - val_root_mean_squared_error: 9776.8252\n",
      "Epoch 999/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1919.6925 - root_mean_squared_error: 7437.2144 - val_loss: 2089.6113 - val_root_mean_squared_error: 9908.8760\n",
      "Epoch 1000/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1942.5371 - root_mean_squared_error: 7346.7651 - val_loss: 2133.8806 - val_root_mean_squared_error: 10097.7666\n",
      "Epoch 1001/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1942.1691 - root_mean_squared_error: 7404.4512 - val_loss: 2098.0222 - val_root_mean_squared_error: 9831.6904\n",
      "Epoch 1002/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1907.2101 - root_mean_squared_error: 7390.9521 - val_loss: 2092.3164 - val_root_mean_squared_error: 9847.1621\n",
      "Epoch 1003/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1904.9990 - root_mean_squared_error: 7437.9629 - val_loss: 2127.0845 - val_root_mean_squared_error: 9669.1094\n",
      "Epoch 1004/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1940.4734 - root_mean_squared_error: 7479.2383 - val_loss: 2069.1294 - val_root_mean_squared_error: 9950.8887\n",
      "Epoch 1005/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1896.7327 - root_mean_squared_error: 7411.4639 - val_loss: 2087.7454 - val_root_mean_squared_error: 9864.8643\n",
      "Epoch 1006/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1894.2922 - root_mean_squared_error: 7386.2837 - val_loss: 2078.6882 - val_root_mean_squared_error: 9886.9033\n",
      "Epoch 1007/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1920.1368 - root_mean_squared_error: 7505.6753 - val_loss: 2115.6194 - val_root_mean_squared_error: 9901.6660\n",
      "Epoch 1008/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1905.3213 - root_mean_squared_error: 7409.3916 - val_loss: 2107.2554 - val_root_mean_squared_error: 10022.3008\n",
      "Epoch 1009/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1899.1173 - root_mean_squared_error: 7401.6611 - val_loss: 2093.6956 - val_root_mean_squared_error: 9963.5469\n",
      "Epoch 1010/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1903.2867 - root_mean_squared_error: 7452.3076 - val_loss: 2086.4673 - val_root_mean_squared_error: 9796.1885\n",
      "Epoch 1011/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1896.6841 - root_mean_squared_error: 7376.9399 - val_loss: 2098.6885 - val_root_mean_squared_error: 9854.4678\n",
      "Epoch 1012/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1895.0237 - root_mean_squared_error: 7396.1514 - val_loss: 2103.0300 - val_root_mean_squared_error: 10012.3096\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1013/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1902.4517 - root_mean_squared_error: 7413.1450 - val_loss: 2095.2358 - val_root_mean_squared_error: 9966.9570\n",
      "Epoch 1014/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1898.0944 - root_mean_squared_error: 7362.9238 - val_loss: 2085.4097 - val_root_mean_squared_error: 9666.8125\n",
      "Epoch 1015/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.5029 - root_mean_squared_error: 7366.4595 - val_loss: 2074.8589 - val_root_mean_squared_error: 9705.6104\n",
      "Epoch 1016/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1905.2484 - root_mean_squared_error: 7376.4902 - val_loss: 2089.3213 - val_root_mean_squared_error: 9746.1504\n",
      "Epoch 1017/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1900.3257 - root_mean_squared_error: 7444.6162 - val_loss: 2093.9639 - val_root_mean_squared_error: 9874.4434\n",
      "Epoch 1018/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1904.0758 - root_mean_squared_error: 7419.6987 - val_loss: 2098.3389 - val_root_mean_squared_error: 9923.1758\n",
      "Epoch 1019/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1948.9080 - root_mean_squared_error: 7422.8394 - val_loss: 2114.4946 - val_root_mean_squared_error: 9926.4043\n",
      "Epoch 1020/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1932.7574 - root_mean_squared_error: 7391.4766 - val_loss: 2075.2363 - val_root_mean_squared_error: 9816.9541\n",
      "Epoch 1021/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1905.8995 - root_mean_squared_error: 7389.4531 - val_loss: 2072.9363 - val_root_mean_squared_error: 9880.0215\n",
      "Epoch 1022/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1902.4873 - root_mean_squared_error: 7371.8516 - val_loss: 2099.3196 - val_root_mean_squared_error: 9793.7207\n",
      "Epoch 1023/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1933.5762 - root_mean_squared_error: 7484.8423 - val_loss: 2132.8911 - val_root_mean_squared_error: 9641.6309\n",
      "Epoch 1024/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1937.5675 - root_mean_squared_error: 7451.3574 - val_loss: 2088.8447 - val_root_mean_squared_error: 9860.1650\n",
      "Epoch 1025/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1908.8485 - root_mean_squared_error: 7316.4321 - val_loss: 2094.6316 - val_root_mean_squared_error: 9710.3438\n",
      "Epoch 1026/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1905.4139 - root_mean_squared_error: 7384.6719 - val_loss: 2078.5771 - val_root_mean_squared_error: 9855.7344\n",
      "Epoch 1027/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1906.7849 - root_mean_squared_error: 7465.2344 - val_loss: 2098.1663 - val_root_mean_squared_error: 10006.3457\n",
      "Epoch 1028/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1902.8474 - root_mean_squared_error: 7389.6821 - val_loss: 2108.5007 - val_root_mean_squared_error: 9831.2471\n",
      "Epoch 1029/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1886.4414 - root_mean_squared_error: 7336.3887 - val_loss: 2097.3201 - val_root_mean_squared_error: 9560.0166\n",
      "Epoch 1030/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1908.9358 - root_mean_squared_error: 7329.2378 - val_loss: 2056.9409 - val_root_mean_squared_error: 9763.3486\n",
      "Epoch 1031/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1936.0134 - root_mean_squared_error: 7430.5317 - val_loss: 2065.8337 - val_root_mean_squared_error: 9737.2646\n",
      "Epoch 1032/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1902.4805 - root_mean_squared_error: 7359.5327 - val_loss: 2097.1738 - val_root_mean_squared_error: 9754.8936\n",
      "Epoch 1033/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1932.0103 - root_mean_squared_error: 7451.0312 - val_loss: 2080.1873 - val_root_mean_squared_error: 10021.6836\n",
      "Epoch 1034/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1893.6771 - root_mean_squared_error: 7378.5029 - val_loss: 2097.6604 - val_root_mean_squared_error: 9857.9912\n",
      "Epoch 1035/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1890.1602 - root_mean_squared_error: 7371.1816 - val_loss: 2090.8384 - val_root_mean_squared_error: 9950.4697\n",
      "Epoch 1036/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1894.2954 - root_mean_squared_error: 7422.0645 - val_loss: 2097.0454 - val_root_mean_squared_error: 9866.4883\n",
      "Epoch 1037/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1903.8302 - root_mean_squared_error: 7432.0010 - val_loss: 2091.9392 - val_root_mean_squared_error: 10057.2295\n",
      "Epoch 1038/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1919.5798 - root_mean_squared_error: 7440.2036 - val_loss: 2078.6365 - val_root_mean_squared_error: 9751.7920\n",
      "Epoch 1039/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1897.3807 - root_mean_squared_error: 7409.7656 - val_loss: 2085.0137 - val_root_mean_squared_error: 9788.0684\n",
      "Epoch 1040/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1912.0863 - root_mean_squared_error: 7394.9946 - val_loss: 2082.3638 - val_root_mean_squared_error: 9862.2227\n",
      "Epoch 1041/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1903.3344 - root_mean_squared_error: 7394.1504 - val_loss: 2087.0872 - val_root_mean_squared_error: 9914.8047\n",
      "Epoch 1042/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1901.7622 - root_mean_squared_error: 7384.1318 - val_loss: 2082.8992 - val_root_mean_squared_error: 9967.0244\n",
      "Epoch 1043/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.5044 - root_mean_squared_error: 7402.0215 - val_loss: 2090.8713 - val_root_mean_squared_error: 9722.9102\n",
      "Epoch 1044/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1925.2030 - root_mean_squared_error: 7395.2153 - val_loss: 2103.2390 - val_root_mean_squared_error: 9493.2832\n",
      "Epoch 1045/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1912.3805 - root_mean_squared_error: 7305.5415 - val_loss: 2060.0942 - val_root_mean_squared_error: 9718.1211\n",
      "Epoch 1046/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1889.6490 - root_mean_squared_error: 7363.1113 - val_loss: 2071.6814 - val_root_mean_squared_error: 9706.0166\n",
      "Epoch 1047/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1896.1337 - root_mean_squared_error: 7361.4424 - val_loss: 2085.7441 - val_root_mean_squared_error: 9866.6875\n",
      "Epoch 1048/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1899.1327 - root_mean_squared_error: 7362.5859 - val_loss: 2093.2480 - val_root_mean_squared_error: 9713.4697\n",
      "Epoch 1049/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1889.5426 - root_mean_squared_error: 7385.2642 - val_loss: 2071.8591 - val_root_mean_squared_error: 9962.0938\n",
      "Epoch 1050/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1894.8669 - root_mean_squared_error: 7420.2090 - val_loss: 2086.5884 - val_root_mean_squared_error: 9864.3320\n",
      "Epoch 1051/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1889.5470 - root_mean_squared_error: 7367.8735 - val_loss: 2059.7930 - val_root_mean_squared_error: 9973.3027\n",
      "Epoch 1052/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1905.5530 - root_mean_squared_error: 7436.2769 - val_loss: 2099.2310 - val_root_mean_squared_error: 9555.6865\n",
      "Epoch 1053/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1902.2715 - root_mean_squared_error: 7324.6274 - val_loss: 2063.6519 - val_root_mean_squared_error: 9703.4268\n",
      "Epoch 1054/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1900.2928 - root_mean_squared_error: 7411.7227 - val_loss: 2082.2864 - val_root_mean_squared_error: 9757.1680\n",
      "Epoch 1055/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1896.8450 - root_mean_squared_error: 7400.6118 - val_loss: 2072.5579 - val_root_mean_squared_error: 9860.5615\n",
      "Epoch 1056/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1900.3746 - root_mean_squared_error: 7424.3433 - val_loss: 2080.7622 - val_root_mean_squared_error: 9736.7920\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1057/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1892.3041 - root_mean_squared_error: 7356.8506 - val_loss: 2086.1426 - val_root_mean_squared_error: 9728.8701\n",
      "Epoch 1058/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1899.9866 - root_mean_squared_error: 7383.5757 - val_loss: 2081.9961 - val_root_mean_squared_error: 9666.5303\n",
      "Epoch 1059/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1901.6541 - root_mean_squared_error: 7334.3013 - val_loss: 2069.4468 - val_root_mean_squared_error: 9698.0410\n",
      "Epoch 1060/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1909.5985 - root_mean_squared_error: 7368.4868 - val_loss: 2080.5288 - val_root_mean_squared_error: 9713.7959\n",
      "Epoch 1061/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1901.9409 - root_mean_squared_error: 7334.5400 - val_loss: 2096.7595 - val_root_mean_squared_error: 9827.2754\n",
      "Epoch 1062/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1918.1149 - root_mean_squared_error: 7386.5547 - val_loss: 2071.5408 - val_root_mean_squared_error: 9738.8857\n",
      "Epoch 1063/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1906.0648 - root_mean_squared_error: 7396.0117 - val_loss: 2074.8230 - val_root_mean_squared_error: 9783.4189\n",
      "Epoch 1064/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1906.0355 - root_mean_squared_error: 7402.8467 - val_loss: 2061.8516 - val_root_mean_squared_error: 9914.4541\n",
      "Epoch 1065/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1893.1854 - root_mean_squared_error: 7394.0381 - val_loss: 2074.6316 - val_root_mean_squared_error: 9747.6768\n",
      "Epoch 1066/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1899.2573 - root_mean_squared_error: 7405.0552 - val_loss: 2078.3872 - val_root_mean_squared_error: 9841.5039\n",
      "Epoch 1067/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1886.1580 - root_mean_squared_error: 7385.0718 - val_loss: 2067.2883 - val_root_mean_squared_error: 9852.5400\n",
      "Epoch 1068/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1886.2544 - root_mean_squared_error: 7366.3481 - val_loss: 2060.2734 - val_root_mean_squared_error: 9880.7949\n",
      "Epoch 1069/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1914.2368 - root_mean_squared_error: 7412.8062 - val_loss: 2073.4883 - val_root_mean_squared_error: 9700.2988\n",
      "Epoch 1070/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1894.8408 - root_mean_squared_error: 7329.6606 - val_loss: 2086.2402 - val_root_mean_squared_error: 9789.0000\n",
      "Epoch 1071/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1886.5308 - root_mean_squared_error: 7356.6372 - val_loss: 2066.0032 - val_root_mean_squared_error: 9852.1982\n",
      "Epoch 1072/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1888.6665 - root_mean_squared_error: 7404.5752 - val_loss: 2071.8057 - val_root_mean_squared_error: 9758.0420\n",
      "Epoch 1073/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1903.8315 - root_mean_squared_error: 7330.7017 - val_loss: 2088.5059 - val_root_mean_squared_error: 9776.9307\n",
      "Epoch 1074/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1910.6052 - root_mean_squared_error: 7367.9072 - val_loss: 2063.5579 - val_root_mean_squared_error: 9886.4941\n",
      "Epoch 1075/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1896.2577 - root_mean_squared_error: 7416.9790 - val_loss: 2081.0566 - val_root_mean_squared_error: 9795.4561\n",
      "Epoch 1076/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1888.9498 - root_mean_squared_error: 7400.0938 - val_loss: 2059.8708 - val_root_mean_squared_error: 9955.0068\n",
      "Epoch 1077/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1910.8671 - root_mean_squared_error: 7425.6899 - val_loss: 2064.4607 - val_root_mean_squared_error: 9854.5195\n",
      "Epoch 1078/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1925.5638 - root_mean_squared_error: 7416.4824 - val_loss: 2119.3560 - val_root_mean_squared_error: 9568.2441\n",
      "Epoch 1079/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1909.3136 - root_mean_squared_error: 7317.7246 - val_loss: 2087.0701 - val_root_mean_squared_error: 9803.7510\n",
      "Epoch 1080/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1915.4814 - root_mean_squared_error: 7470.8633 - val_loss: 2073.1262 - val_root_mean_squared_error: 10198.2480\n",
      "Epoch 1081/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1919.4636 - root_mean_squared_error: 7455.7603 - val_loss: 2078.8857 - val_root_mean_squared_error: 9998.0000\n",
      "Epoch 1082/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1900.4862 - root_mean_squared_error: 7372.2134 - val_loss: 2091.0852 - val_root_mean_squared_error: 9602.9268\n",
      "Epoch 1083/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1887.1842 - root_mean_squared_error: 7316.9570 - val_loss: 2046.8298 - val_root_mean_squared_error: 9758.1143\n",
      "Epoch 1084/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1890.6196 - root_mean_squared_error: 7360.2246 - val_loss: 2061.3137 - val_root_mean_squared_error: 9732.5791\n",
      "Epoch 1085/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1882.6238 - root_mean_squared_error: 7384.5972 - val_loss: 2062.0330 - val_root_mean_squared_error: 9794.9746\n",
      "Epoch 1086/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1892.0354 - root_mean_squared_error: 7385.9521 - val_loss: 2066.7920 - val_root_mean_squared_error: 9771.7852\n",
      "Epoch 1087/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1883.5591 - root_mean_squared_error: 7359.1392 - val_loss: 2059.9714 - val_root_mean_squared_error: 9671.8506\n",
      "Epoch 1088/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1884.4287 - root_mean_squared_error: 7357.7607 - val_loss: 2064.6599 - val_root_mean_squared_error: 9852.7490\n",
      "Epoch 1089/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1884.7245 - root_mean_squared_error: 7358.7275 - val_loss: 2071.8381 - val_root_mean_squared_error: 9635.5166\n",
      "Epoch 1090/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1906.2026 - root_mean_squared_error: 7362.5366 - val_loss: 2058.7671 - val_root_mean_squared_error: 9819.6982\n",
      "Epoch 1091/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1893.3132 - root_mean_squared_error: 7365.4937 - val_loss: 2058.6262 - val_root_mean_squared_error: 9739.3252\n",
      "Epoch 1092/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1874.0850 - root_mean_squared_error: 7357.3101 - val_loss: 2097.2742 - val_root_mean_squared_error: 9470.6328\n",
      "Epoch 1093/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1904.8805 - root_mean_squared_error: 7298.7749 - val_loss: 2063.6606 - val_root_mean_squared_error: 9752.1855\n",
      "Epoch 1094/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1903.4543 - root_mean_squared_error: 7373.7837 - val_loss: 2075.7666 - val_root_mean_squared_error: 9431.3594\n",
      "Epoch 1095/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1905.6000 - root_mean_squared_error: 7342.4873 - val_loss: 2044.6705 - val_root_mean_squared_error: 9679.5469\n",
      "Epoch 1096/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1922.2404 - root_mean_squared_error: 7355.4297 - val_loss: 2061.6194 - val_root_mean_squared_error: 9766.3252\n",
      "Epoch 1097/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1935.9021 - root_mean_squared_error: 7377.1050 - val_loss: 2098.7412 - val_root_mean_squared_error: 9508.9873\n",
      "Epoch 1098/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1894.3223 - root_mean_squared_error: 7355.6655 - val_loss: 2059.0117 - val_root_mean_squared_error: 9609.3760\n",
      "Epoch 1099/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1887.1051 - root_mean_squared_error: 7352.3550 - val_loss: 2051.6599 - val_root_mean_squared_error: 9706.9531\n",
      "Epoch 1100/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1888.2034 - root_mean_squared_error: 7384.7456 - val_loss: 2078.6340 - val_root_mean_squared_error: 9525.0898\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1101/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1911.4316 - root_mean_squared_error: 7397.6567 - val_loss: 2056.5527 - val_root_mean_squared_error: 9533.0693\n",
      "Epoch 1102/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1901.2887 - root_mean_squared_error: 7300.6382 - val_loss: 2056.3491 - val_root_mean_squared_error: 9627.6650\n",
      "Epoch 1103/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1889.4962 - root_mean_squared_error: 7330.6743 - val_loss: 2068.1912 - val_root_mean_squared_error: 9398.6982\n",
      "Epoch 1104/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1918.5189 - root_mean_squared_error: 7421.4351 - val_loss: 2036.2673 - val_root_mean_squared_error: 9612.7656\n",
      "Epoch 1105/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1888.8760 - root_mean_squared_error: 7306.9912 - val_loss: 2059.2449 - val_root_mean_squared_error: 9566.3701\n",
      "Epoch 1106/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1883.6893 - root_mean_squared_error: 7324.7266 - val_loss: 2033.9252 - val_root_mean_squared_error: 9658.7891\n",
      "Epoch 1107/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1884.9485 - root_mean_squared_error: 7322.3467 - val_loss: 2059.5916 - val_root_mean_squared_error: 9630.1934\n",
      "Epoch 1108/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1881.2040 - root_mean_squared_error: 7352.0073 - val_loss: 2044.8149 - val_root_mean_squared_error: 9654.3574\n",
      "Epoch 1109/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1888.5656 - root_mean_squared_error: 7328.9468 - val_loss: 2066.0554 - val_root_mean_squared_error: 9597.8662\n",
      "Epoch 1110/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1887.3293 - root_mean_squared_error: 7297.8228 - val_loss: 2045.8231 - val_root_mean_squared_error: 9514.1455\n",
      "Epoch 1111/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1881.6260 - root_mean_squared_error: 7402.8477 - val_loss: 2056.6804 - val_root_mean_squared_error: 9485.2344\n",
      "Epoch 1112/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1893.7042 - root_mean_squared_error: 7318.9004 - val_loss: 2045.0359 - val_root_mean_squared_error: 9580.6621\n",
      "Epoch 1113/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1884.1467 - root_mean_squared_error: 7332.8662 - val_loss: 2027.9257 - val_root_mean_squared_error: 9552.1016\n",
      "Epoch 1114/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1890.6873 - root_mean_squared_error: 7397.1201 - val_loss: 2051.4431 - val_root_mean_squared_error: 9660.0898\n",
      "Epoch 1115/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1890.9188 - root_mean_squared_error: 7370.3481 - val_loss: 2069.0703 - val_root_mean_squared_error: 9643.4033\n",
      "Epoch 1116/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1886.2028 - root_mean_squared_error: 7332.6494 - val_loss: 2066.9834 - val_root_mean_squared_error: 9826.1309\n",
      "Epoch 1117/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1901.6940 - root_mean_squared_error: 7371.9263 - val_loss: 2040.6870 - val_root_mean_squared_error: 9694.0879\n",
      "Epoch 1118/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1892.7224 - root_mean_squared_error: 7323.5488 - val_loss: 2038.3774 - val_root_mean_squared_error: 9449.9463\n",
      "Epoch 1119/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1883.5768 - root_mean_squared_error: 7290.1445 - val_loss: 2031.1165 - val_root_mean_squared_error: 9417.2764\n",
      "Epoch 1120/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1887.7075 - root_mean_squared_error: 7326.6006 - val_loss: 2026.0858 - val_root_mean_squared_error: 9519.8711\n",
      "Epoch 1121/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1881.1056 - root_mean_squared_error: 7356.6094 - val_loss: 2037.0905 - val_root_mean_squared_error: 9679.4922\n",
      "Epoch 1122/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1881.3436 - root_mean_squared_error: 7317.7686 - val_loss: 2048.2830 - val_root_mean_squared_error: 9640.1338\n",
      "Epoch 1123/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1911.8527 - root_mean_squared_error: 7430.5264 - val_loss: 2072.2698 - val_root_mean_squared_error: 9317.1172\n",
      "Epoch 1124/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1882.7405 - root_mean_squared_error: 7287.5610 - val_loss: 2026.8654 - val_root_mean_squared_error: 9553.7402\n",
      "Epoch 1125/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1884.5397 - root_mean_squared_error: 7387.1699 - val_loss: 2046.4575 - val_root_mean_squared_error: 9709.1973\n",
      "Epoch 1126/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1879.4933 - root_mean_squared_error: 7357.7168 - val_loss: 2061.4666 - val_root_mean_squared_error: 9525.6553\n",
      "Epoch 1127/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1893.4998 - root_mean_squared_error: 7328.2842 - val_loss: 2028.7533 - val_root_mean_squared_error: 9515.5645\n",
      "Epoch 1128/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1896.2141 - root_mean_squared_error: 7359.7808 - val_loss: 2023.9260 - val_root_mean_squared_error: 9564.2510\n",
      "Epoch 1129/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1882.9581 - root_mean_squared_error: 7348.0083 - val_loss: 2056.5186 - val_root_mean_squared_error: 9642.5664\n",
      "Epoch 1130/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1891.3975 - root_mean_squared_error: 7300.5229 - val_loss: 2037.2502 - val_root_mean_squared_error: 9505.7275\n",
      "Epoch 1131/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1906.4961 - root_mean_squared_error: 7320.2646 - val_loss: 2031.1222 - val_root_mean_squared_error: 9533.5215\n",
      "Epoch 1132/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1879.5549 - root_mean_squared_error: 7361.3613 - val_loss: 2046.1368 - val_root_mean_squared_error: 9613.7852\n",
      "Epoch 1133/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1876.9692 - root_mean_squared_error: 7329.8110 - val_loss: 2037.9197 - val_root_mean_squared_error: 9661.8936\n",
      "Epoch 1134/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1877.8030 - root_mean_squared_error: 7332.0366 - val_loss: 2046.6626 - val_root_mean_squared_error: 9485.8965\n",
      "Epoch 1135/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1894.2947 - root_mean_squared_error: 7349.6167 - val_loss: 2035.9403 - val_root_mean_squared_error: 9392.8486\n",
      "Epoch 1136/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1876.8702 - root_mean_squared_error: 7233.0815 - val_loss: 2049.6968 - val_root_mean_squared_error: 9635.6562\n",
      "Epoch 1137/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1914.4814 - root_mean_squared_error: 7349.5928 - val_loss: 2040.0195 - val_root_mean_squared_error: 9521.1045\n",
      "Epoch 1138/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1892.6511 - root_mean_squared_error: 7377.0405 - val_loss: 2067.8269 - val_root_mean_squared_error: 9452.4482\n",
      "Epoch 1139/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1892.2343 - root_mean_squared_error: 7376.5020 - val_loss: 2040.7689 - val_root_mean_squared_error: 9733.9883\n",
      "Epoch 1140/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1878.8179 - root_mean_squared_error: 7322.3135 - val_loss: 2037.9948 - val_root_mean_squared_error: 9528.8262\n",
      "Epoch 1141/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1887.5588 - root_mean_squared_error: 7368.0117 - val_loss: 2054.5383 - val_root_mean_squared_error: 9422.8789\n",
      "Epoch 1142/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1901.4662 - root_mean_squared_error: 7343.8184 - val_loss: 2033.3109 - val_root_mean_squared_error: 9690.9541\n",
      "Epoch 1143/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1889.7622 - root_mean_squared_error: 7289.2803 - val_loss: 2013.5332 - val_root_mean_squared_error: 9452.3574\n",
      "Epoch 1144/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1896.7662 - root_mean_squared_error: 7335.0908 - val_loss: 2016.9637 - val_root_mean_squared_error: 9500.2031\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1145/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1909.4526 - root_mean_squared_error: 7408.4814 - val_loss: 2045.7755 - val_root_mean_squared_error: 9356.2168\n",
      "Epoch 1146/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1889.7733 - root_mean_squared_error: 7345.5962 - val_loss: 2013.5905 - val_root_mean_squared_error: 9708.4414\n",
      "Epoch 1147/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1878.1553 - root_mean_squared_error: 7366.9385 - val_loss: 2049.0232 - val_root_mean_squared_error: 9545.7939\n",
      "Epoch 1148/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1881.4692 - root_mean_squared_error: 7296.6816 - val_loss: 2029.9518 - val_root_mean_squared_error: 9456.6797\n",
      "Epoch 1149/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1879.3359 - root_mean_squared_error: 7365.0107 - val_loss: 2028.0436 - val_root_mean_squared_error: 9643.5703\n",
      "Epoch 1150/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1885.8813 - root_mean_squared_error: 7306.3589 - val_loss: 2039.5106 - val_root_mean_squared_error: 9393.6025\n",
      "Epoch 1151/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1886.3955 - root_mean_squared_error: 7285.2388 - val_loss: 2014.6274 - val_root_mean_squared_error: 9471.2754\n",
      "Epoch 1152/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1884.8654 - root_mean_squared_error: 7346.0288 - val_loss: 2037.9602 - val_root_mean_squared_error: 9585.4180\n",
      "Epoch 1153/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1878.9690 - root_mean_squared_error: 7289.7085 - val_loss: 2068.0918 - val_root_mean_squared_error: 9193.9678\n",
      "Epoch 1154/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1900.8059 - root_mean_squared_error: 7315.8418 - val_loss: 2012.5134 - val_root_mean_squared_error: 9397.5820\n",
      "Epoch 1155/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1898.9703 - root_mean_squared_error: 7304.8101 - val_loss: 2012.5096 - val_root_mean_squared_error: 9623.2178\n",
      "Epoch 1156/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1889.0563 - root_mean_squared_error: 7327.7783 - val_loss: 2031.3253 - val_root_mean_squared_error: 9584.0078\n",
      "Epoch 1157/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1880.0953 - root_mean_squared_error: 7314.8765 - val_loss: 2033.0707 - val_root_mean_squared_error: 9370.3984\n",
      "Epoch 1158/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1893.8286 - root_mean_squared_error: 7375.5425 - val_loss: 2030.6866 - val_root_mean_squared_error: 9371.9033\n",
      "Epoch 1159/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1891.8015 - root_mean_squared_error: 7269.2944 - val_loss: 2041.7445 - val_root_mean_squared_error: 9583.6123\n",
      "Epoch 1160/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1894.0782 - root_mean_squared_error: 7295.4951 - val_loss: 2015.2626 - val_root_mean_squared_error: 9314.3203\n",
      "Epoch 1161/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1895.4642 - root_mean_squared_error: 7317.5215 - val_loss: 2003.0176 - val_root_mean_squared_error: 9402.3486\n",
      "Epoch 1162/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1894.0146 - root_mean_squared_error: 7332.8271 - val_loss: 2035.7742 - val_root_mean_squared_error: 9555.7129\n",
      "Epoch 1163/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1874.3618 - root_mean_squared_error: 7298.1860 - val_loss: 2020.3665 - val_root_mean_squared_error: 9561.4170\n",
      "Epoch 1164/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1875.8868 - root_mean_squared_error: 7320.6006 - val_loss: 2045.0869 - val_root_mean_squared_error: 9258.8584\n",
      "Epoch 1165/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1878.3345 - root_mean_squared_error: 7260.0186 - val_loss: 2015.5803 - val_root_mean_squared_error: 9399.0586\n",
      "Epoch 1166/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1883.0253 - root_mean_squared_error: 7355.8584 - val_loss: 2016.4030 - val_root_mean_squared_error: 9501.5938\n",
      "Epoch 1167/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1873.9456 - root_mean_squared_error: 7283.7798 - val_loss: 2036.0077 - val_root_mean_squared_error: 9489.5723\n",
      "Epoch 1168/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1876.2084 - root_mean_squared_error: 7321.6489 - val_loss: 2013.7256 - val_root_mean_squared_error: 9577.1484\n",
      "Epoch 1169/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1869.0162 - root_mean_squared_error: 7316.9087 - val_loss: 2027.4225 - val_root_mean_squared_error: 9433.2100\n",
      "Epoch 1170/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1874.0079 - root_mean_squared_error: 7269.7627 - val_loss: 2020.0765 - val_root_mean_squared_error: 9477.2256\n",
      "Epoch 1171/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1872.9351 - root_mean_squared_error: 7321.7344 - val_loss: 2019.6442 - val_root_mean_squared_error: 9438.9824\n",
      "Epoch 1172/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1865.1116 - root_mean_squared_error: 7286.4087 - val_loss: 2022.8378 - val_root_mean_squared_error: 9481.9121\n",
      "Epoch 1173/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1879.2244 - root_mean_squared_error: 7293.9819 - val_loss: 2015.7740 - val_root_mean_squared_error: 9326.9541\n",
      "Epoch 1174/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1870.9958 - root_mean_squared_error: 7270.1187 - val_loss: 2020.7930 - val_root_mean_squared_error: 9312.8994\n",
      "Epoch 1175/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1877.9137 - root_mean_squared_error: 7352.5767 - val_loss: 2013.5641 - val_root_mean_squared_error: 9602.3145\n",
      "Epoch 1176/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1880.9481 - root_mean_squared_error: 7386.2734 - val_loss: 2041.4406 - val_root_mean_squared_error: 9415.2412\n",
      "Epoch 1177/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1894.5835 - root_mean_squared_error: 7258.9272 - val_loss: 2034.5894 - val_root_mean_squared_error: 9435.1797\n",
      "Epoch 1178/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1868.7081 - root_mean_squared_error: 7264.1729 - val_loss: 2010.5959 - val_root_mean_squared_error: 9525.9287\n",
      "Epoch 1179/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1869.0317 - root_mean_squared_error: 7306.2500 - val_loss: 2027.6541 - val_root_mean_squared_error: 9280.7744\n",
      "Epoch 1180/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1882.8047 - root_mean_squared_error: 7237.7656 - val_loss: 2022.1769 - val_root_mean_squared_error: 9622.8359\n",
      "Epoch 1181/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1910.8274 - root_mean_squared_error: 7368.6021 - val_loss: 2004.6459 - val_root_mean_squared_error: 9376.2334\n",
      "Epoch 1182/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1864.6416 - root_mean_squared_error: 7265.3032 - val_loss: 2022.3835 - val_root_mean_squared_error: 9417.4385\n",
      "Epoch 1183/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1866.5121 - root_mean_squared_error: 7319.7373 - val_loss: 2020.3882 - val_root_mean_squared_error: 9417.0859\n",
      "Epoch 1184/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1870.2565 - root_mean_squared_error: 7266.0679 - val_loss: 2007.9652 - val_root_mean_squared_error: 9342.1826\n",
      "Epoch 1185/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1866.0095 - root_mean_squared_error: 7287.0771 - val_loss: 1995.7192 - val_root_mean_squared_error: 9489.9170\n",
      "Epoch 1186/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1878.0768 - root_mean_squared_error: 7274.7012 - val_loss: 2046.2607 - val_root_mean_squared_error: 9109.4287\n",
      "Epoch 1187/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1883.3232 - root_mean_squared_error: 7288.7109 - val_loss: 2001.4769 - val_root_mean_squared_error: 9295.2666\n",
      "Epoch 1188/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1870.8201 - root_mean_squared_error: 7313.5474 - val_loss: 2002.1472 - val_root_mean_squared_error: 9383.9492\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1189/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1865.4518 - root_mean_squared_error: 7272.1602 - val_loss: 2018.9120 - val_root_mean_squared_error: 9453.1201\n",
      "Epoch 1190/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1874.1208 - root_mean_squared_error: 7285.5664 - val_loss: 2030.4559 - val_root_mean_squared_error: 9259.3633\n",
      "Epoch 1191/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1866.7023 - root_mean_squared_error: 7286.4331 - val_loss: 2020.5557 - val_root_mean_squared_error: 9319.4121\n",
      "Epoch 1192/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1878.0016 - root_mean_squared_error: 7254.7734 - val_loss: 2005.1602 - val_root_mean_squared_error: 9353.8711\n",
      "Epoch 1193/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1883.0924 - root_mean_squared_error: 7245.6470 - val_loss: 2017.3356 - val_root_mean_squared_error: 9442.1328\n",
      "Epoch 1194/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1918.3690 - root_mean_squared_error: 7358.5142 - val_loss: 2041.0427 - val_root_mean_squared_error: 9176.2451\n",
      "Epoch 1195/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1887.7063 - root_mean_squared_error: 7273.7617 - val_loss: 2015.1501 - val_root_mean_squared_error: 9272.1484\n",
      "Epoch 1196/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1891.5818 - root_mean_squared_error: 7320.2832 - val_loss: 2013.1368 - val_root_mean_squared_error: 9612.4111\n",
      "Epoch 1197/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1869.8126 - root_mean_squared_error: 7203.3164 - val_loss: 2027.1866 - val_root_mean_squared_error: 9240.3408\n",
      "Epoch 1198/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1885.2938 - root_mean_squared_error: 7271.1841 - val_loss: 2004.4844 - val_root_mean_squared_error: 9138.1836\n",
      "Epoch 1199/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1885.1448 - root_mean_squared_error: 7207.1743 - val_loss: 2032.3092 - val_root_mean_squared_error: 9405.5244\n",
      "Epoch 1200/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1888.4697 - root_mean_squared_error: 7291.0713 - val_loss: 1996.3218 - val_root_mean_squared_error: 9384.1338\n",
      "Epoch 1201/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1858.9524 - root_mean_squared_error: 7292.1934 - val_loss: 2026.5151 - val_root_mean_squared_error: 9249.3184\n",
      "Epoch 1202/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1861.7848 - root_mean_squared_error: 7202.1582 - val_loss: 2005.6873 - val_root_mean_squared_error: 9324.1846\n",
      "Epoch 1203/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1871.2843 - root_mean_squared_error: 7290.2329 - val_loss: 2003.3851 - val_root_mean_squared_error: 9241.5850\n",
      "Epoch 1204/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1876.9657 - root_mean_squared_error: 7242.6968 - val_loss: 2010.1241 - val_root_mean_squared_error: 9458.0186\n",
      "Epoch 1205/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1862.0659 - root_mean_squared_error: 7246.1572 - val_loss: 1995.7908 - val_root_mean_squared_error: 9216.9756\n",
      "Epoch 1206/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1860.0385 - root_mean_squared_error: 7268.4927 - val_loss: 2001.1033 - val_root_mean_squared_error: 9217.1455\n",
      "Epoch 1207/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1875.2717 - root_mean_squared_error: 7276.5464 - val_loss: 1993.1952 - val_root_mean_squared_error: 9363.7920\n",
      "Epoch 1208/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1864.2833 - root_mean_squared_error: 7251.7783 - val_loss: 2018.3342 - val_root_mean_squared_error: 9467.6943\n",
      "Epoch 1209/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1889.0962 - root_mean_squared_error: 7295.9160 - val_loss: 1985.4885 - val_root_mean_squared_error: 9225.3770\n",
      "Epoch 1210/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1873.0466 - root_mean_squared_error: 7258.4565 - val_loss: 1975.0433 - val_root_mean_squared_error: 9235.0967\n",
      "Epoch 1211/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1874.8418 - root_mean_squared_error: 7226.8198 - val_loss: 1994.0400 - val_root_mean_squared_error: 9129.7051\n",
      "Epoch 1212/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1862.8545 - root_mean_squared_error: 7208.8076 - val_loss: 2003.1245 - val_root_mean_squared_error: 9326.8145\n",
      "Epoch 1213/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1897.2378 - root_mean_squared_error: 7273.5845 - val_loss: 2002.2231 - val_root_mean_squared_error: 9075.3379\n",
      "Epoch 1214/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1865.5472 - root_mean_squared_error: 7259.5566 - val_loss: 1982.1300 - val_root_mean_squared_error: 9332.0176\n",
      "Epoch 1215/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1860.7806 - root_mean_squared_error: 7242.0562 - val_loss: 1988.8876 - val_root_mean_squared_error: 9295.8340\n",
      "Epoch 1216/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1871.2792 - root_mean_squared_error: 7230.1196 - val_loss: 1991.7283 - val_root_mean_squared_error: 9186.4609\n",
      "Epoch 1217/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1860.8965 - root_mean_squared_error: 7249.2769 - val_loss: 1991.7595 - val_root_mean_squared_error: 9241.9941\n",
      "Epoch 1218/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1853.4786 - root_mean_squared_error: 7230.2949 - val_loss: 1995.9364 - val_root_mean_squared_error: 9406.0117\n",
      "Epoch 1219/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1878.4073 - root_mean_squared_error: 7278.2715 - val_loss: 2000.0096 - val_root_mean_squared_error: 9150.4795\n",
      "Epoch 1220/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1865.6177 - root_mean_squared_error: 7270.3247 - val_loss: 1981.7119 - val_root_mean_squared_error: 9370.0732\n",
      "Epoch 1221/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1877.4974 - root_mean_squared_error: 7281.4316 - val_loss: 2001.3075 - val_root_mean_squared_error: 9053.7051\n",
      "Epoch 1222/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1877.7587 - root_mean_squared_error: 7235.3242 - val_loss: 1994.3264 - val_root_mean_squared_error: 9092.6885\n",
      "Epoch 1223/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1869.4249 - root_mean_squared_error: 7214.2026 - val_loss: 1986.9989 - val_root_mean_squared_error: 9212.7432\n",
      "Epoch 1224/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1862.4542 - root_mean_squared_error: 7200.9565 - val_loss: 1992.8175 - val_root_mean_squared_error: 9250.9580\n",
      "Epoch 1225/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1857.6202 - root_mean_squared_error: 7226.8594 - val_loss: 1973.9679 - val_root_mean_squared_error: 9161.2354\n",
      "Epoch 1226/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1851.0405 - root_mean_squared_error: 7255.8999 - val_loss: 1993.7764 - val_root_mean_squared_error: 9255.0166\n",
      "Epoch 1227/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1854.2574 - root_mean_squared_error: 7234.0435 - val_loss: 1979.3246 - val_root_mean_squared_error: 9281.0615\n",
      "Epoch 1228/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1867.6902 - root_mean_squared_error: 7239.3306 - val_loss: 1981.1379 - val_root_mean_squared_error: 9154.7939\n",
      "Epoch 1229/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1864.3055 - root_mean_squared_error: 7247.1338 - val_loss: 1984.0458 - val_root_mean_squared_error: 9113.5762\n",
      "Epoch 1230/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1845.3542 - root_mean_squared_error: 7211.0703 - val_loss: 1968.9692 - val_root_mean_squared_error: 9229.4434\n",
      "Epoch 1231/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1836.0016 - root_mean_squared_error: 7179.3535 - val_loss: 1998.8059 - val_root_mean_squared_error: 8884.6992\n",
      "Epoch 1232/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1868.0870 - root_mean_squared_error: 7155.1211 - val_loss: 1969.5951 - val_root_mean_squared_error: 8852.0918\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1233/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1856.0194 - root_mean_squared_error: 7155.3745 - val_loss: 1969.7645 - val_root_mean_squared_error: 9104.5625\n",
      "Epoch 1234/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1870.7982 - root_mean_squared_error: 7200.2847 - val_loss: 1979.0911 - val_root_mean_squared_error: 9195.5557\n",
      "Epoch 1235/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1842.1691 - root_mean_squared_error: 7248.0908 - val_loss: 1968.8789 - val_root_mean_squared_error: 9011.5488\n",
      "Epoch 1236/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1850.3112 - root_mean_squared_error: 7211.9097 - val_loss: 1977.0063 - val_root_mean_squared_error: 8972.9131\n",
      "Epoch 1237/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1867.4098 - root_mean_squared_error: 7150.3271 - val_loss: 1992.2139 - val_root_mean_squared_error: 9331.3047\n",
      "Epoch 1238/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1895.0018 - root_mean_squared_error: 7182.9141 - val_loss: 1973.6278 - val_root_mean_squared_error: 9194.3916\n",
      "Epoch 1239/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1839.4546 - root_mean_squared_error: 7178.7837 - val_loss: 1962.7458 - val_root_mean_squared_error: 8864.1699\n",
      "Epoch 1240/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1857.4182 - root_mean_squared_error: 7167.1333 - val_loss: 1940.8926 - val_root_mean_squared_error: 8897.5830\n",
      "Epoch 1241/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1852.9664 - root_mean_squared_error: 7187.2612 - val_loss: 1956.8204 - val_root_mean_squared_error: 9102.2656\n",
      "Epoch 1242/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1855.3207 - root_mean_squared_error: 7241.0854 - val_loss: 1955.3719 - val_root_mean_squared_error: 9105.0352\n",
      "Epoch 1243/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1850.9259 - root_mean_squared_error: 7266.6406 - val_loss: 1976.2793 - val_root_mean_squared_error: 9263.0127\n",
      "Epoch 1244/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1856.1432 - root_mean_squared_error: 7237.6597 - val_loss: 1970.1851 - val_root_mean_squared_error: 9185.7207\n",
      "Epoch 1245/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1845.4124 - root_mean_squared_error: 7206.7935 - val_loss: 1959.5836 - val_root_mean_squared_error: 8946.3848\n",
      "Epoch 1246/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1873.2867 - root_mean_squared_error: 7220.6758 - val_loss: 1945.5920 - val_root_mean_squared_error: 8756.8789\n",
      "Epoch 1247/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1869.7776 - root_mean_squared_error: 7250.2646 - val_loss: 1948.8081 - val_root_mean_squared_error: 9108.6133\n",
      "Epoch 1248/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1857.1113 - root_mean_squared_error: 7204.6626 - val_loss: 1984.3655 - val_root_mean_squared_error: 9076.1533\n",
      "Epoch 1249/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1866.1257 - root_mean_squared_error: 7186.6016 - val_loss: 1970.3153 - val_root_mean_squared_error: 9233.7725\n",
      "Epoch 1250/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1853.5825 - root_mean_squared_error: 7200.4487 - val_loss: 1969.0581 - val_root_mean_squared_error: 8896.7197\n",
      "Epoch 1251/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1886.0186 - root_mean_squared_error: 7308.3047 - val_loss: 1958.1292 - val_root_mean_squared_error: 9016.0859\n",
      "Epoch 1252/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1847.1477 - root_mean_squared_error: 7192.1108 - val_loss: 1952.2742 - val_root_mean_squared_error: 9062.6670\n",
      "Epoch 1253/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1860.0176 - root_mean_squared_error: 7226.4448 - val_loss: 1961.7130 - val_root_mean_squared_error: 9257.0137\n",
      "Epoch 1254/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1866.8463 - root_mean_squared_error: 7274.6968 - val_loss: 1980.7201 - val_root_mean_squared_error: 9048.6143\n",
      "Epoch 1255/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1849.6046 - root_mean_squared_error: 7220.8438 - val_loss: 1974.7755 - val_root_mean_squared_error: 9068.7500\n",
      "Epoch 1256/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1850.2725 - root_mean_squared_error: 7164.3384 - val_loss: 1977.7517 - val_root_mean_squared_error: 8672.5332\n",
      "Epoch 1257/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1859.4418 - root_mean_squared_error: 7140.0190 - val_loss: 1944.3944 - val_root_mean_squared_error: 8847.7598\n",
      "Epoch 1258/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1863.4507 - root_mean_squared_error: 7157.1641 - val_loss: 1960.1318 - val_root_mean_squared_error: 8957.5039\n",
      "Epoch 1259/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1883.9000 - root_mean_squared_error: 7178.4351 - val_loss: 1967.7634 - val_root_mean_squared_error: 8592.1787\n",
      "Epoch 1260/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1865.0634 - root_mean_squared_error: 7115.1431 - val_loss: 1935.2102 - val_root_mean_squared_error: 8837.0762\n",
      "Epoch 1261/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1877.5450 - root_mean_squared_error: 7292.6929 - val_loss: 1954.5420 - val_root_mean_squared_error: 8940.8594\n",
      "Epoch 1262/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1879.6377 - root_mean_squared_error: 7200.5752 - val_loss: 1977.6932 - val_root_mean_squared_error: 9113.3955\n",
      "Epoch 1263/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1855.7952 - root_mean_squared_error: 7195.4390 - val_loss: 1945.0551 - val_root_mean_squared_error: 8939.5605\n",
      "Epoch 1264/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1858.3696 - root_mean_squared_error: 7194.8545 - val_loss: 1944.2740 - val_root_mean_squared_error: 8987.6758\n",
      "Epoch 1265/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1839.9066 - root_mean_squared_error: 7151.5547 - val_loss: 1949.4038 - val_root_mean_squared_error: 8927.9453\n",
      "Epoch 1266/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1846.2502 - root_mean_squared_error: 7187.2910 - val_loss: 1942.7676 - val_root_mean_squared_error: 8961.7129\n",
      "Epoch 1267/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1840.2072 - root_mean_squared_error: 7237.0366 - val_loss: 1961.6412 - val_root_mean_squared_error: 9038.5312\n",
      "Epoch 1268/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1865.5195 - root_mean_squared_error: 7230.5620 - val_loss: 1943.4120 - val_root_mean_squared_error: 9017.3525\n",
      "Epoch 1269/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1851.7145 - root_mean_squared_error: 7196.6094 - val_loss: 1943.8915 - val_root_mean_squared_error: 8843.2949\n",
      "Epoch 1270/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1841.8162 - root_mean_squared_error: 7145.6299 - val_loss: 1936.9406 - val_root_mean_squared_error: 8983.3271\n",
      "Epoch 1271/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1834.9434 - root_mean_squared_error: 7189.1240 - val_loss: 1946.8723 - val_root_mean_squared_error: 9025.8047\n",
      "Epoch 1272/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1838.7052 - root_mean_squared_error: 7191.6724 - val_loss: 1940.5453 - val_root_mean_squared_error: 8918.3281\n",
      "Epoch 1273/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1844.1343 - root_mean_squared_error: 7251.4229 - val_loss: 1952.8134 - val_root_mean_squared_error: 8971.1895\n",
      "Epoch 1274/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1851.3628 - root_mean_squared_error: 7156.0068 - val_loss: 1965.7780 - val_root_mean_squared_error: 9030.7021\n",
      "Epoch 1275/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1848.7104 - root_mean_squared_error: 7194.3330 - val_loss: 1951.3730 - val_root_mean_squared_error: 8881.7344\n",
      "Epoch 1276/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1851.2725 - root_mean_squared_error: 7144.4214 - val_loss: 1944.2887 - val_root_mean_squared_error: 8941.2402\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1277/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1846.8114 - root_mean_squared_error: 7155.8325 - val_loss: 1944.5649 - val_root_mean_squared_error: 8977.1416\n",
      "Epoch 1278/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1849.2197 - root_mean_squared_error: 7098.7451 - val_loss: 1929.3684 - val_root_mean_squared_error: 8852.5879\n",
      "Epoch 1279/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1850.9143 - root_mean_squared_error: 7140.0322 - val_loss: 1923.6655 - val_root_mean_squared_error: 8781.9717\n",
      "Epoch 1280/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1841.3257 - root_mean_squared_error: 7180.5811 - val_loss: 1938.6699 - val_root_mean_squared_error: 8889.2383\n",
      "Epoch 1281/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1836.2889 - root_mean_squared_error: 7144.3086 - val_loss: 1945.1201 - val_root_mean_squared_error: 8797.9561\n",
      "Epoch 1282/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1872.0416 - root_mean_squared_error: 7183.3188 - val_loss: 1960.6096 - val_root_mean_squared_error: 8706.6963\n",
      "Epoch 1283/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1856.0221 - root_mean_squared_error: 7167.2979 - val_loss: 1940.6943 - val_root_mean_squared_error: 8972.9766\n",
      "Epoch 1284/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1843.5421 - root_mean_squared_error: 7123.6372 - val_loss: 1955.8030 - val_root_mean_squared_error: 8969.3379\n",
      "Epoch 1285/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1882.8258 - root_mean_squared_error: 7286.7998 - val_loss: 1960.1069 - val_root_mean_squared_error: 8712.6152\n",
      "Epoch 1286/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1850.6595 - root_mean_squared_error: 7134.4150 - val_loss: 1928.4712 - val_root_mean_squared_error: 8868.9404\n",
      "Epoch 1287/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1854.2139 - root_mean_squared_error: 7174.7520 - val_loss: 1934.3297 - val_root_mean_squared_error: 8948.4170\n",
      "Epoch 1288/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1829.3041 - root_mean_squared_error: 7137.9414 - val_loss: 1941.7812 - val_root_mean_squared_error: 8860.2217\n",
      "Epoch 1289/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1841.7915 - root_mean_squared_error: 7169.1064 - val_loss: 1934.4377 - val_root_mean_squared_error: 8776.9346\n",
      "Epoch 1290/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1837.6884 - root_mean_squared_error: 7110.9946 - val_loss: 1943.7426 - val_root_mean_squared_error: 8573.8418\n",
      "Epoch 1291/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1867.8967 - root_mean_squared_error: 7083.1338 - val_loss: 1915.6587 - val_root_mean_squared_error: 8720.1992\n",
      "Epoch 1292/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1850.6282 - root_mean_squared_error: 7115.9609 - val_loss: 1924.9729 - val_root_mean_squared_error: 8900.8760\n",
      "Epoch 1293/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1838.5549 - root_mean_squared_error: 7149.2764 - val_loss: 1925.5453 - val_root_mean_squared_error: 8900.6553\n",
      "Epoch 1294/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1836.0668 - root_mean_squared_error: 7191.6948 - val_loss: 1931.2111 - val_root_mean_squared_error: 8703.0479\n",
      "Epoch 1295/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1845.6752 - root_mean_squared_error: 7103.6084 - val_loss: 1968.4280 - val_root_mean_squared_error: 8820.5527\n",
      "Epoch 1296/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1861.6058 - root_mean_squared_error: 7146.6318 - val_loss: 1921.4885 - val_root_mean_squared_error: 8821.9258\n",
      "Epoch 1297/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1838.7123 - root_mean_squared_error: 7155.8081 - val_loss: 1929.6768 - val_root_mean_squared_error: 8905.7793\n",
      "Epoch 1298/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1855.3076 - root_mean_squared_error: 7209.9619 - val_loss: 1938.4580 - val_root_mean_squared_error: 8758.2441\n",
      "Epoch 1299/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1863.1914 - root_mean_squared_error: 7144.6890 - val_loss: 1947.3871 - val_root_mean_squared_error: 8970.6543\n",
      "Epoch 1300/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1843.9968 - root_mean_squared_error: 7176.7822 - val_loss: 1943.5277 - val_root_mean_squared_error: 8674.7871\n",
      "Epoch 1301/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1840.3813 - root_mean_squared_error: 7109.7842 - val_loss: 1956.8453 - val_root_mean_squared_error: 8913.4668\n",
      "Epoch 1302/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1879.4476 - root_mean_squared_error: 7172.7373 - val_loss: 1927.3204 - val_root_mean_squared_error: 8720.5264\n",
      "Epoch 1303/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1845.0559 - root_mean_squared_error: 7120.9189 - val_loss: 1927.1423 - val_root_mean_squared_error: 8905.5840\n",
      "Epoch 1304/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1832.7177 - root_mean_squared_error: 7154.0200 - val_loss: 1929.8640 - val_root_mean_squared_error: 8690.2383\n",
      "Epoch 1305/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1833.3009 - root_mean_squared_error: 7111.3774 - val_loss: 1926.9421 - val_root_mean_squared_error: 8865.1064\n",
      "Epoch 1306/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1834.1471 - root_mean_squared_error: 7085.8804 - val_loss: 1930.2379 - val_root_mean_squared_error: 8692.2207\n",
      "Epoch 1307/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1832.1273 - root_mean_squared_error: 7088.6729 - val_loss: 1918.8303 - val_root_mean_squared_error: 8767.4639\n",
      "Epoch 1308/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1832.7775 - root_mean_squared_error: 7130.7393 - val_loss: 1914.9325 - val_root_mean_squared_error: 8685.6436\n",
      "Epoch 1309/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1828.0349 - root_mean_squared_error: 7107.0161 - val_loss: 1920.8409 - val_root_mean_squared_error: 8857.8311\n",
      "Epoch 1310/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1834.2391 - root_mean_squared_error: 7153.6162 - val_loss: 1931.6853 - val_root_mean_squared_error: 8780.8145\n",
      "Epoch 1311/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1829.2496 - root_mean_squared_error: 7099.5356 - val_loss: 1920.1987 - val_root_mean_squared_error: 8629.0312\n",
      "Epoch 1312/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1824.8469 - root_mean_squared_error: 7088.9111 - val_loss: 1915.7963 - val_root_mean_squared_error: 8775.0625\n",
      "Epoch 1313/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1827.2555 - root_mean_squared_error: 7143.1631 - val_loss: 1920.8442 - val_root_mean_squared_error: 8709.4414\n",
      "Epoch 1314/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1847.0381 - root_mean_squared_error: 7069.0845 - val_loss: 1941.1658 - val_root_mean_squared_error: 8682.2441\n",
      "Epoch 1315/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1840.8669 - root_mean_squared_error: 7130.0044 - val_loss: 1904.1681 - val_root_mean_squared_error: 8743.5752\n",
      "Epoch 1316/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1839.9894 - root_mean_squared_error: 7113.9238 - val_loss: 1911.3503 - val_root_mean_squared_error: 8658.1777\n",
      "Epoch 1317/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1826.5432 - root_mean_squared_error: 7087.5098 - val_loss: 1932.6300 - val_root_mean_squared_error: 8780.4805\n",
      "Epoch 1318/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1855.9824 - root_mean_squared_error: 7175.0254 - val_loss: 1904.4080 - val_root_mean_squared_error: 8567.4229\n",
      "Epoch 1319/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1867.0236 - root_mean_squared_error: 7125.0967 - val_loss: 1945.3334 - val_root_mean_squared_error: 8471.3574\n",
      "Epoch 1320/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1856.2461 - root_mean_squared_error: 7153.9849 - val_loss: 1914.5217 - val_root_mean_squared_error: 8815.1572\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1321/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1847.0563 - root_mean_squared_error: 7114.4180 - val_loss: 1919.1721 - val_root_mean_squared_error: 8576.4512\n",
      "Epoch 1322/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1835.2167 - root_mean_squared_error: 7053.6226 - val_loss: 1901.8997 - val_root_mean_squared_error: 8497.2129\n",
      "Epoch 1323/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1829.1538 - root_mean_squared_error: 7072.5176 - val_loss: 1896.0592 - val_root_mean_squared_error: 8542.8359\n",
      "Epoch 1324/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1828.5227 - root_mean_squared_error: 7091.6050 - val_loss: 1905.1490 - val_root_mean_squared_error: 8748.6504\n",
      "Epoch 1325/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1819.3530 - root_mean_squared_error: 7062.0767 - val_loss: 1918.1598 - val_root_mean_squared_error: 8384.2031\n",
      "Epoch 1326/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1828.2794 - root_mean_squared_error: 7048.2036 - val_loss: 1902.6045 - val_root_mean_squared_error: 8713.3096\n",
      "Epoch 1327/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1842.3481 - root_mean_squared_error: 7081.8447 - val_loss: 1903.7368 - val_root_mean_squared_error: 8582.2422\n",
      "Epoch 1328/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1832.0189 - root_mean_squared_error: 7093.6387 - val_loss: 1898.4224 - val_root_mean_squared_error: 8639.9492\n",
      "Epoch 1329/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1833.9224 - root_mean_squared_error: 7135.2891 - val_loss: 1895.4192 - val_root_mean_squared_error: 8648.0195\n",
      "Epoch 1330/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1838.1195 - root_mean_squared_error: 7081.2607 - val_loss: 1932.7089 - val_root_mean_squared_error: 8667.1299\n",
      "Epoch 1331/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1854.6116 - root_mean_squared_error: 7167.9004 - val_loss: 1906.0957 - val_root_mean_squared_error: 8472.2207\n",
      "Epoch 1332/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1860.9955 - root_mean_squared_error: 7148.0908 - val_loss: 1927.7762 - val_root_mean_squared_error: 8621.2715\n",
      "Epoch 1333/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1853.8049 - root_mean_squared_error: 7126.0410 - val_loss: 1918.2502 - val_root_mean_squared_error: 8854.4014\n",
      "Epoch 1334/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1844.8641 - root_mean_squared_error: 7052.7676 - val_loss: 1920.2974 - val_root_mean_squared_error: 8448.3086\n",
      "Epoch 1335/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1831.6094 - root_mean_squared_error: 7055.1885 - val_loss: 1911.6831 - val_root_mean_squared_error: 8249.2256\n",
      "Epoch 1336/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1830.8604 - root_mean_squared_error: 7000.0015 - val_loss: 1882.0808 - val_root_mean_squared_error: 8375.9824\n",
      "Epoch 1337/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1819.0930 - root_mean_squared_error: 7058.6836 - val_loss: 1883.3550 - val_root_mean_squared_error: 8498.6436\n",
      "Epoch 1338/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1817.7970 - root_mean_squared_error: 7078.2939 - val_loss: 1887.3301 - val_root_mean_squared_error: 8545.5547\n",
      "Epoch 1339/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1818.4187 - root_mean_squared_error: 7079.6914 - val_loss: 1898.1829 - val_root_mean_squared_error: 8518.3867\n",
      "Epoch 1340/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1824.3030 - root_mean_squared_error: 7027.4814 - val_loss: 1886.8577 - val_root_mean_squared_error: 8417.8857\n",
      "Epoch 1341/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1813.2241 - root_mean_squared_error: 7041.8384 - val_loss: 1879.5427 - val_root_mean_squared_error: 8547.2793\n",
      "Epoch 1342/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1829.4165 - root_mean_squared_error: 7100.9155 - val_loss: 1889.1490 - val_root_mean_squared_error: 8469.7168\n",
      "Epoch 1343/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1833.5074 - root_mean_squared_error: 7064.3662 - val_loss: 1891.0134 - val_root_mean_squared_error: 8436.2588\n",
      "Epoch 1344/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1839.2560 - root_mean_squared_error: 7057.1802 - val_loss: 1898.7322 - val_root_mean_squared_error: 8691.8467\n",
      "Epoch 1345/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1844.1272 - root_mean_squared_error: 7149.1377 - val_loss: 1890.7949 - val_root_mean_squared_error: 8570.4512\n",
      "Epoch 1346/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1816.4268 - root_mean_squared_error: 7088.4204 - val_loss: 1894.0836 - val_root_mean_squared_error: 8419.5947\n",
      "Epoch 1347/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1822.6914 - root_mean_squared_error: 7048.3237 - val_loss: 1900.9547 - val_root_mean_squared_error: 8477.1299\n",
      "Epoch 1348/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1813.0073 - root_mean_squared_error: 7021.6978 - val_loss: 1868.3948 - val_root_mean_squared_error: 8484.7627\n",
      "Epoch 1349/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1825.4708 - root_mean_squared_error: 7099.4370 - val_loss: 1894.8698 - val_root_mean_squared_error: 8351.7900\n",
      "Epoch 1350/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1856.4172 - root_mean_squared_error: 7059.2886 - val_loss: 1876.3878 - val_root_mean_squared_error: 8375.2588\n",
      "Epoch 1351/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1844.5322 - root_mean_squared_error: 7068.9961 - val_loss: 1896.5302 - val_root_mean_squared_error: 8670.9326\n",
      "Epoch 1352/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1835.0928 - root_mean_squared_error: 7072.0015 - val_loss: 1890.2333 - val_root_mean_squared_error: 8366.9648\n",
      "Epoch 1353/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1816.6138 - root_mean_squared_error: 7027.9326 - val_loss: 1868.7272 - val_root_mean_squared_error: 8476.5371\n",
      "Epoch 1354/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1838.3184 - root_mean_squared_error: 7081.1289 - val_loss: 1901.4791 - val_root_mean_squared_error: 8224.0117\n",
      "Epoch 1355/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1831.7474 - root_mean_squared_error: 6977.7412 - val_loss: 1865.6538 - val_root_mean_squared_error: 8395.2979\n",
      "Epoch 1356/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1828.8923 - root_mean_squared_error: 7053.3696 - val_loss: 1851.4175 - val_root_mean_squared_error: 8466.7266\n",
      "Epoch 1357/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1824.4518 - root_mean_squared_error: 7106.9985 - val_loss: 1883.5559 - val_root_mean_squared_error: 8549.4189\n",
      "Epoch 1358/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1825.1108 - root_mean_squared_error: 7072.5366 - val_loss: 1885.0537 - val_root_mean_squared_error: 8273.6289\n",
      "Epoch 1359/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1816.8530 - root_mean_squared_error: 7029.8208 - val_loss: 1891.2856 - val_root_mean_squared_error: 8473.7246\n",
      "Epoch 1360/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1812.1537 - root_mean_squared_error: 7026.9253 - val_loss: 1877.9835 - val_root_mean_squared_error: 8263.7949\n",
      "Epoch 1361/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1817.8092 - root_mean_squared_error: 7096.6611 - val_loss: 1867.9857 - val_root_mean_squared_error: 8423.5010\n",
      "Epoch 1362/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1803.9066 - root_mean_squared_error: 6992.1914 - val_loss: 1878.3704 - val_root_mean_squared_error: 8133.2930\n",
      "Epoch 1363/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1815.2668 - root_mean_squared_error: 7023.8267 - val_loss: 1855.3281 - val_root_mean_squared_error: 8265.9688\n",
      "Epoch 1364/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1809.4832 - root_mean_squared_error: 6990.1958 - val_loss: 1862.8544 - val_root_mean_squared_error: 8151.9185\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1365/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1805.2115 - root_mean_squared_error: 7008.2275 - val_loss: 1861.8336 - val_root_mean_squared_error: 8294.5576\n",
      "Epoch 1366/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1814.0594 - root_mean_squared_error: 7041.4478 - val_loss: 1858.5488 - val_root_mean_squared_error: 8319.2363\n",
      "Epoch 1367/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1804.9437 - root_mean_squared_error: 7027.6738 - val_loss: 1863.5214 - val_root_mean_squared_error: 8405.4170\n",
      "Epoch 1368/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1801.9858 - root_mean_squared_error: 7019.6938 - val_loss: 1864.6155 - val_root_mean_squared_error: 8114.8403\n",
      "Epoch 1369/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1815.9501 - root_mean_squared_error: 6952.0859 - val_loss: 1854.9238 - val_root_mean_squared_error: 8406.9658\n",
      "Epoch 1370/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1829.5754 - root_mean_squared_error: 7065.2002 - val_loss: 1855.3331 - val_root_mean_squared_error: 8539.7637\n",
      "Epoch 1371/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1827.9692 - root_mean_squared_error: 7048.1270 - val_loss: 1875.2760 - val_root_mean_squared_error: 8365.6182\n",
      "Epoch 1372/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1814.3949 - root_mean_squared_error: 6990.1812 - val_loss: 1856.9159 - val_root_mean_squared_error: 8261.5156\n",
      "Epoch 1373/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1810.6509 - root_mean_squared_error: 7012.4785 - val_loss: 1855.8057 - val_root_mean_squared_error: 8251.1875\n",
      "Epoch 1374/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1803.7343 - root_mean_squared_error: 6973.6841 - val_loss: 1844.8961 - val_root_mean_squared_error: 8053.7173\n",
      "Epoch 1375/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1816.6553 - root_mean_squared_error: 7009.6187 - val_loss: 1851.3188 - val_root_mean_squared_error: 8104.5879\n",
      "Epoch 1376/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1807.4697 - root_mean_squared_error: 6980.9810 - val_loss: 1860.6198 - val_root_mean_squared_error: 8274.3740\n",
      "Epoch 1377/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1820.6826 - root_mean_squared_error: 7054.1987 - val_loss: 1861.7045 - val_root_mean_squared_error: 8227.0625\n",
      "Epoch 1378/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1808.2644 - root_mean_squared_error: 7016.9194 - val_loss: 1848.4556 - val_root_mean_squared_error: 8180.5586\n",
      "Epoch 1379/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1806.5204 - root_mean_squared_error: 6989.4614 - val_loss: 1862.1774 - val_root_mean_squared_error: 8106.8623\n",
      "Epoch 1380/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1809.4604 - root_mean_squared_error: 7029.6118 - val_loss: 1844.5367 - val_root_mean_squared_error: 8073.8320\n",
      "Epoch 1381/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1843.6021 - root_mean_squared_error: 7125.1714 - val_loss: 1852.3759 - val_root_mean_squared_error: 8381.2520\n",
      "Epoch 1382/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1831.7087 - root_mean_squared_error: 7046.8765 - val_loss: 1890.7618 - val_root_mean_squared_error: 8199.1279\n",
      "Epoch 1383/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1825.0294 - root_mean_squared_error: 6987.5679 - val_loss: 1839.7952 - val_root_mean_squared_error: 8378.5684\n",
      "Epoch 1384/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1834.6368 - root_mean_squared_error: 7067.4194 - val_loss: 1864.3871 - val_root_mean_squared_error: 8022.5459\n",
      "Epoch 1385/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1853.3923 - root_mean_squared_error: 7038.1494 - val_loss: 1856.7889 - val_root_mean_squared_error: 8307.9199\n",
      "Epoch 1386/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1847.4329 - root_mean_squared_error: 7065.0596 - val_loss: 1866.0392 - val_root_mean_squared_error: 8292.7051\n",
      "Epoch 1387/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1836.8734 - root_mean_squared_error: 6976.5293 - val_loss: 1872.0765 - val_root_mean_squared_error: 8071.8438\n",
      "Epoch 1388/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1823.6858 - root_mean_squared_error: 6996.4644 - val_loss: 1841.5062 - val_root_mean_squared_error: 8310.9072\n",
      "Epoch 1389/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1815.9805 - root_mean_squared_error: 6993.9292 - val_loss: 1859.2572 - val_root_mean_squared_error: 8109.4727\n",
      "Epoch 1390/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1811.1301 - root_mean_squared_error: 7006.8271 - val_loss: 1831.2731 - val_root_mean_squared_error: 8191.3892\n",
      "Epoch 1391/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1815.1819 - root_mean_squared_error: 6975.3750 - val_loss: 1859.1910 - val_root_mean_squared_error: 8072.8540\n",
      "Epoch 1392/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1805.8944 - root_mean_squared_error: 7045.4658 - val_loss: 1837.6796 - val_root_mean_squared_error: 8212.9170\n",
      "Epoch 1393/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1831.9326 - root_mean_squared_error: 6969.2319 - val_loss: 1882.7064 - val_root_mean_squared_error: 8498.8086\n",
      "Epoch 1394/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1825.7146 - root_mean_squared_error: 7067.3652 - val_loss: 1849.0518 - val_root_mean_squared_error: 8053.6152\n",
      "Epoch 1395/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1815.7271 - root_mean_squared_error: 6967.6851 - val_loss: 1836.4569 - val_root_mean_squared_error: 8208.8877\n",
      "Epoch 1396/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1805.1112 - root_mean_squared_error: 7009.4351 - val_loss: 1863.0249 - val_root_mean_squared_error: 8119.5776\n",
      "Epoch 1397/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1793.4185 - root_mean_squared_error: 6972.4502 - val_loss: 1838.9789 - val_root_mean_squared_error: 8169.2593\n",
      "Epoch 1398/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1804.6698 - root_mean_squared_error: 6973.3896 - val_loss: 1844.9792 - val_root_mean_squared_error: 8083.5747\n",
      "Epoch 1399/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1822.5630 - root_mean_squared_error: 7038.6636 - val_loss: 1843.7618 - val_root_mean_squared_error: 8165.7046\n",
      "Epoch 1400/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1804.9581 - root_mean_squared_error: 6973.7812 - val_loss: 1848.6538 - val_root_mean_squared_error: 7836.7456\n",
      "Epoch 1401/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1830.1866 - root_mean_squared_error: 7006.8252 - val_loss: 1818.7296 - val_root_mean_squared_error: 8072.2349\n",
      "Epoch 1402/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1794.4594 - root_mean_squared_error: 6924.0801 - val_loss: 1850.1187 - val_root_mean_squared_error: 8149.7642\n",
      "Epoch 1403/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1801.2731 - root_mean_squared_error: 6991.7598 - val_loss: 1840.2003 - val_root_mean_squared_error: 7933.2861\n",
      "Epoch 1404/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1807.0739 - root_mean_squared_error: 6950.0786 - val_loss: 1838.9254 - val_root_mean_squared_error: 8042.5029\n",
      "Epoch 1405/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1822.1400 - root_mean_squared_error: 6941.7070 - val_loss: 1841.3097 - val_root_mean_squared_error: 7815.6021\n",
      "Epoch 1406/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1864.3140 - root_mean_squared_error: 7064.2651 - val_loss: 1860.0986 - val_root_mean_squared_error: 7628.3149\n",
      "Epoch 1407/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1860.2632 - root_mean_squared_error: 7042.4902 - val_loss: 1825.4430 - val_root_mean_squared_error: 8083.9775\n",
      "Epoch 1408/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1814.8065 - root_mean_squared_error: 7024.2598 - val_loss: 1921.5685 - val_root_mean_squared_error: 8430.3730\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1409/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1935.3590 - root_mean_squared_error: 6935.5854 - val_loss: 1869.3503 - val_root_mean_squared_error: 7831.2002\n",
      "Epoch 1410/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1824.9042 - root_mean_squared_error: 6938.8501 - val_loss: 1837.1278 - val_root_mean_squared_error: 7904.0815\n",
      "Epoch 1411/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1808.7839 - root_mean_squared_error: 7008.7417 - val_loss: 1842.9409 - val_root_mean_squared_error: 8085.6377\n",
      "Epoch 1412/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1808.0664 - root_mean_squared_error: 6913.3135 - val_loss: 1831.2577 - val_root_mean_squared_error: 7942.6108\n",
      "Epoch 1413/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1791.8351 - root_mean_squared_error: 6922.9336 - val_loss: 1834.5659 - val_root_mean_squared_error: 8061.1865\n",
      "Epoch 1414/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1809.9172 - root_mean_squared_error: 6964.2793 - val_loss: 1843.7977 - val_root_mean_squared_error: 7921.7163\n",
      "Epoch 1415/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1818.7202 - root_mean_squared_error: 6949.1377 - val_loss: 1801.2467 - val_root_mean_squared_error: 7869.1250\n",
      "Epoch 1416/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1808.0233 - root_mean_squared_error: 6983.9663 - val_loss: 1829.3142 - val_root_mean_squared_error: 8109.7524\n",
      "Epoch 1417/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1824.7058 - root_mean_squared_error: 7043.0435 - val_loss: 1864.3822 - val_root_mean_squared_error: 7575.0264\n",
      "Epoch 1418/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1857.7389 - root_mean_squared_error: 6973.4141 - val_loss: 1830.1604 - val_root_mean_squared_error: 8016.2783\n",
      "Epoch 1419/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1818.9374 - root_mean_squared_error: 6950.2744 - val_loss: 1862.6523 - val_root_mean_squared_error: 8049.5879\n",
      "Epoch 1420/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1827.6627 - root_mean_squared_error: 6906.1431 - val_loss: 1839.9258 - val_root_mean_squared_error: 8120.3877\n",
      "Epoch 1421/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1809.0573 - root_mean_squared_error: 6982.4287 - val_loss: 1843.5258 - val_root_mean_squared_error: 7915.8721\n",
      "Epoch 1422/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1802.4718 - root_mean_squared_error: 6932.0527 - val_loss: 1829.8887 - val_root_mean_squared_error: 7829.1147\n",
      "Epoch 1423/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1802.4445 - root_mean_squared_error: 6955.2246 - val_loss: 1842.4521 - val_root_mean_squared_error: 8218.0469\n",
      "Epoch 1424/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1834.0607 - root_mean_squared_error: 7034.1099 - val_loss: 1819.1658 - val_root_mean_squared_error: 8019.7471\n",
      "Epoch 1425/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1788.9249 - root_mean_squared_error: 6959.6992 - val_loss: 1820.6393 - val_root_mean_squared_error: 8079.0312\n",
      "Epoch 1426/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1795.4937 - root_mean_squared_error: 6963.8892 - val_loss: 1841.9056 - val_root_mean_squared_error: 7967.1216\n",
      "Epoch 1427/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1800.2678 - root_mean_squared_error: 6943.9561 - val_loss: 1823.1836 - val_root_mean_squared_error: 7912.8315\n",
      "Epoch 1428/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1801.0448 - root_mean_squared_error: 6954.0449 - val_loss: 1826.1967 - val_root_mean_squared_error: 7845.9399\n",
      "Epoch 1429/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1788.6183 - root_mean_squared_error: 6932.4712 - val_loss: 1822.5299 - val_root_mean_squared_error: 8141.2710\n",
      "Epoch 1430/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1798.2513 - root_mean_squared_error: 6913.4526 - val_loss: 1822.6451 - val_root_mean_squared_error: 7865.6470\n",
      "Epoch 1431/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1792.7861 - root_mean_squared_error: 6950.0781 - val_loss: 1824.5842 - val_root_mean_squared_error: 7966.5459\n",
      "Epoch 1432/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1810.4780 - root_mean_squared_error: 6995.6953 - val_loss: 1836.3813 - val_root_mean_squared_error: 7885.0220\n",
      "Epoch 1433/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1802.4402 - root_mean_squared_error: 6955.6123 - val_loss: 1809.9229 - val_root_mean_squared_error: 8075.1372\n",
      "Epoch 1434/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1819.0524 - root_mean_squared_error: 6955.5308 - val_loss: 1826.5243 - val_root_mean_squared_error: 7800.8066\n",
      "Epoch 1435/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1808.3754 - root_mean_squared_error: 6938.0181 - val_loss: 1820.6005 - val_root_mean_squared_error: 7937.6069\n",
      "Epoch 1436/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1789.0128 - root_mean_squared_error: 6948.8330 - val_loss: 1822.8204 - val_root_mean_squared_error: 7857.3667\n",
      "Epoch 1437/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1821.4523 - root_mean_squared_error: 6931.1416 - val_loss: 1800.2327 - val_root_mean_squared_error: 7755.5845\n",
      "Epoch 1438/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1821.0162 - root_mean_squared_error: 6945.7036 - val_loss: 1809.6627 - val_root_mean_squared_error: 7647.5161\n",
      "Epoch 1439/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1827.7755 - root_mean_squared_error: 6963.7026 - val_loss: 1805.9427 - val_root_mean_squared_error: 7908.0078\n",
      "Epoch 1440/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1801.2026 - root_mean_squared_error: 6960.1914 - val_loss: 1809.3978 - val_root_mean_squared_error: 7967.9170\n",
      "Epoch 1441/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1803.5563 - root_mean_squared_error: 6912.0635 - val_loss: 1823.3806 - val_root_mean_squared_error: 7886.6519\n",
      "Epoch 1442/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1807.8296 - root_mean_squared_error: 6953.2061 - val_loss: 1831.1981 - val_root_mean_squared_error: 7808.0620\n",
      "Epoch 1443/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1837.8124 - root_mean_squared_error: 6981.6030 - val_loss: 1797.5898 - val_root_mean_squared_error: 7742.6797\n",
      "Epoch 1444/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1805.6765 - root_mean_squared_error: 6971.5479 - val_loss: 1801.5736 - val_root_mean_squared_error: 7885.4629\n",
      "Epoch 1445/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1786.2053 - root_mean_squared_error: 6946.3149 - val_loss: 1807.5634 - val_root_mean_squared_error: 7957.3262\n",
      "Epoch 1446/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1807.5514 - root_mean_squared_error: 6985.7837 - val_loss: 1802.7682 - val_root_mean_squared_error: 7521.0996\n",
      "Epoch 1447/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1799.3580 - root_mean_squared_error: 6877.0879 - val_loss: 1789.4248 - val_root_mean_squared_error: 7810.4351\n",
      "Epoch 1448/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1791.6700 - root_mean_squared_error: 6950.3911 - val_loss: 1839.4952 - val_root_mean_squared_error: 7814.8154\n",
      "Epoch 1449/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1807.9342 - root_mean_squared_error: 6929.3013 - val_loss: 1811.1117 - val_root_mean_squared_error: 7942.9238\n",
      "Epoch 1450/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1791.8687 - root_mean_squared_error: 6895.4419 - val_loss: 1796.3998 - val_root_mean_squared_error: 7770.4429\n",
      "Epoch 1451/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1811.0345 - root_mean_squared_error: 6972.8188 - val_loss: 1830.9609 - val_root_mean_squared_error: 7895.2251\n",
      "Epoch 1452/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1799.2896 - root_mean_squared_error: 6972.9580 - val_loss: 1822.1722 - val_root_mean_squared_error: 7897.4746\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1453/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1784.8748 - root_mean_squared_error: 6898.5171 - val_loss: 1800.9437 - val_root_mean_squared_error: 7708.2847\n",
      "Epoch 1454/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1788.0294 - root_mean_squared_error: 6942.0410 - val_loss: 1803.2920 - val_root_mean_squared_error: 7802.9482\n",
      "Epoch 1455/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1792.4977 - root_mean_squared_error: 6903.2734 - val_loss: 1798.4916 - val_root_mean_squared_error: 7538.2603\n",
      "Epoch 1456/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1794.8801 - root_mean_squared_error: 6928.7700 - val_loss: 1793.4772 - val_root_mean_squared_error: 7701.8789\n",
      "Epoch 1457/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1814.7948 - root_mean_squared_error: 7039.6724 - val_loss: 1801.3757 - val_root_mean_squared_error: 7684.0938\n",
      "Epoch 1458/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1791.3716 - root_mean_squared_error: 6895.9941 - val_loss: 1797.7982 - val_root_mean_squared_error: 7856.0864\n",
      "Epoch 1459/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1801.1288 - root_mean_squared_error: 6923.6123 - val_loss: 1810.4398 - val_root_mean_squared_error: 8037.9556\n",
      "Epoch 1460/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1816.3018 - root_mean_squared_error: 6982.9521 - val_loss: 1800.7589 - val_root_mean_squared_error: 7787.1611\n",
      "Epoch 1461/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1785.1116 - root_mean_squared_error: 6916.9971 - val_loss: 1811.6143 - val_root_mean_squared_error: 7462.5659\n",
      "Epoch 1462/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1806.9789 - root_mean_squared_error: 6974.6201 - val_loss: 1804.6876 - val_root_mean_squared_error: 7840.6104\n",
      "Epoch 1463/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1805.1631 - root_mean_squared_error: 6883.8140 - val_loss: 1793.0116 - val_root_mean_squared_error: 7895.3345\n",
      "Epoch 1464/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1802.4930 - root_mean_squared_error: 6917.5688 - val_loss: 1810.3105 - val_root_mean_squared_error: 7633.5752\n",
      "Epoch 1465/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1806.2145 - root_mean_squared_error: 6900.6821 - val_loss: 1801.9196 - val_root_mean_squared_error: 7657.2856\n",
      "Epoch 1466/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1795.7456 - root_mean_squared_error: 6876.4434 - val_loss: 1777.3787 - val_root_mean_squared_error: 7919.9819\n",
      "Epoch 1467/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1778.2020 - root_mean_squared_error: 6924.0278 - val_loss: 1807.7747 - val_root_mean_squared_error: 7680.3857\n",
      "Epoch 1468/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1791.3092 - root_mean_squared_error: 6916.6963 - val_loss: 1789.2358 - val_root_mean_squared_error: 7463.0488\n",
      "Epoch 1469/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1797.7660 - root_mean_squared_error: 6827.9902 - val_loss: 1783.2863 - val_root_mean_squared_error: 7779.8589\n",
      "Epoch 1470/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1781.5029 - root_mean_squared_error: 6924.2490 - val_loss: 1789.2468 - val_root_mean_squared_error: 7838.4341\n",
      "Epoch 1471/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1783.4044 - root_mean_squared_error: 6965.6226 - val_loss: 1795.0884 - val_root_mean_squared_error: 7707.7485\n",
      "Epoch 1472/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1782.6317 - root_mean_squared_error: 6886.2212 - val_loss: 1797.7079 - val_root_mean_squared_error: 7852.4316\n",
      "Epoch 1473/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1777.1899 - root_mean_squared_error: 6897.2949 - val_loss: 1802.2064 - val_root_mean_squared_error: 7620.1899\n",
      "Epoch 1474/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1780.7074 - root_mean_squared_error: 6882.6318 - val_loss: 1783.7161 - val_root_mean_squared_error: 7765.0518\n",
      "Epoch 1475/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1794.7488 - root_mean_squared_error: 6916.8589 - val_loss: 1791.6803 - val_root_mean_squared_error: 7790.7178\n",
      "Epoch 1476/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1793.1294 - root_mean_squared_error: 6910.5854 - val_loss: 1794.0228 - val_root_mean_squared_error: 7655.9561\n",
      "Epoch 1477/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1807.4502 - root_mean_squared_error: 6901.2349 - val_loss: 1784.8132 - val_root_mean_squared_error: 7470.1064\n",
      "Epoch 1478/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1788.4305 - root_mean_squared_error: 6824.0815 - val_loss: 1782.9779 - val_root_mean_squared_error: 7737.5444\n",
      "Epoch 1479/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1790.6366 - root_mean_squared_error: 6901.5181 - val_loss: 1806.8770 - val_root_mean_squared_error: 7776.4497\n",
      "Epoch 1480/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1782.1454 - root_mean_squared_error: 6873.8623 - val_loss: 1776.7891 - val_root_mean_squared_error: 7704.1772\n",
      "Epoch 1481/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1806.7200 - root_mean_squared_error: 6920.4565 - val_loss: 1791.1748 - val_root_mean_squared_error: 7506.5586\n",
      "Epoch 1482/2000\n",
      "10/10 [==============================] - 0s 16ms/step - loss: 1804.3085 - root_mean_squared_error: 6892.7256 - val_loss: 1791.8468 - val_root_mean_squared_error: 7550.6367\n",
      "Epoch 1483/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1795.9677 - root_mean_squared_error: 6877.4575 - val_loss: 1782.4814 - val_root_mean_squared_error: 7634.2734\n",
      "Epoch 1484/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1780.3866 - root_mean_squared_error: 6863.2446 - val_loss: 1798.4883 - val_root_mean_squared_error: 7634.5332\n",
      "Epoch 1485/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1807.2209 - root_mean_squared_error: 6817.7476 - val_loss: 1769.9332 - val_root_mean_squared_error: 7720.2827\n",
      "Epoch 1486/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1815.0162 - root_mean_squared_error: 6905.3242 - val_loss: 1780.5325 - val_root_mean_squared_error: 7471.3174\n",
      "Epoch 1487/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1777.8680 - root_mean_squared_error: 6893.2275 - val_loss: 1772.5289 - val_root_mean_squared_error: 7865.3960\n",
      "Epoch 1488/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1792.8918 - root_mean_squared_error: 6939.8267 - val_loss: 1788.9739 - val_root_mean_squared_error: 7400.7637\n",
      "Epoch 1489/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1783.9600 - root_mean_squared_error: 6803.5859 - val_loss: 1781.3240 - val_root_mean_squared_error: 7702.3237\n",
      "Epoch 1490/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1819.5375 - root_mean_squared_error: 6909.0322 - val_loss: 1785.1771 - val_root_mean_squared_error: 7742.0557\n",
      "Epoch 1491/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1801.1882 - root_mean_squared_error: 6857.7832 - val_loss: 1765.4065 - val_root_mean_squared_error: 7531.1709\n",
      "Epoch 1492/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1804.5551 - root_mean_squared_error: 6938.4189 - val_loss: 1778.7090 - val_root_mean_squared_error: 7520.6689\n",
      "Epoch 1493/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1777.7395 - root_mean_squared_error: 6875.0908 - val_loss: 1772.3253 - val_root_mean_squared_error: 7561.4238\n",
      "Epoch 1494/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1800.4751 - root_mean_squared_error: 6877.1924 - val_loss: 1787.9375 - val_root_mean_squared_error: 7812.6489\n",
      "Epoch 1495/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1790.8452 - root_mean_squared_error: 6878.5435 - val_loss: 1783.5955 - val_root_mean_squared_error: 7479.9316\n",
      "Epoch 1496/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1790.2157 - root_mean_squared_error: 6820.3398 - val_loss: 1772.1781 - val_root_mean_squared_error: 7474.4971\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1497/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1796.2970 - root_mean_squared_error: 6882.2441 - val_loss: 1750.7228 - val_root_mean_squared_error: 7467.8145\n",
      "Epoch 1498/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1775.0895 - root_mean_squared_error: 6875.9678 - val_loss: 1772.1748 - val_root_mean_squared_error: 7490.8643\n",
      "Epoch 1499/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1777.8634 - root_mean_squared_error: 6846.8140 - val_loss: 1763.3370 - val_root_mean_squared_error: 7541.2896\n",
      "Epoch 1500/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1793.7906 - root_mean_squared_error: 6840.4673 - val_loss: 1765.5333 - val_root_mean_squared_error: 7586.2227\n",
      "Epoch 1501/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1816.0492 - root_mean_squared_error: 6919.4189 - val_loss: 1776.0598 - val_root_mean_squared_error: 7415.9707\n",
      "Epoch 1502/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1800.2277 - root_mean_squared_error: 6843.3618 - val_loss: 1771.8630 - val_root_mean_squared_error: 7509.7241\n",
      "Epoch 1503/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1789.9285 - root_mean_squared_error: 6893.2554 - val_loss: 1802.7152 - val_root_mean_squared_error: 7604.0254\n",
      "Epoch 1504/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1803.1793 - root_mean_squared_error: 6953.1504 - val_loss: 1769.9084 - val_root_mean_squared_error: 7678.7368\n",
      "Epoch 1505/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1817.8851 - root_mean_squared_error: 6865.1987 - val_loss: 1856.4104 - val_root_mean_squared_error: 7819.0171\n",
      "Epoch 1506/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1879.8929 - root_mean_squared_error: 6925.7598 - val_loss: 1764.9967 - val_root_mean_squared_error: 7472.9453\n",
      "Epoch 1507/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1797.4486 - root_mean_squared_error: 6843.7012 - val_loss: 1755.1758 - val_root_mean_squared_error: 7535.2334\n",
      "Epoch 1508/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1816.2397 - root_mean_squared_error: 6993.7007 - val_loss: 1782.4353 - val_root_mean_squared_error: 7519.0200\n",
      "Epoch 1509/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1815.1726 - root_mean_squared_error: 6783.1929 - val_loss: 1813.3666 - val_root_mean_squared_error: 7581.8125\n",
      "Epoch 1510/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1801.4120 - root_mean_squared_error: 6831.7021 - val_loss: 1762.1001 - val_root_mean_squared_error: 7400.6909\n",
      "Epoch 1511/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1792.0310 - root_mean_squared_error: 6925.8003 - val_loss: 1773.2142 - val_root_mean_squared_error: 7650.8169\n",
      "Epoch 1512/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1772.0317 - root_mean_squared_error: 6866.8882 - val_loss: 1772.7740 - val_root_mean_squared_error: 7485.2266\n",
      "Epoch 1513/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1786.0879 - root_mean_squared_error: 6815.3740 - val_loss: 1765.6416 - val_root_mean_squared_error: 7449.2676\n",
      "Epoch 1514/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1800.5531 - root_mean_squared_error: 6905.4800 - val_loss: 1768.1617 - val_root_mean_squared_error: 7555.1226\n",
      "Epoch 1515/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1783.3807 - root_mean_squared_error: 6892.3564 - val_loss: 1766.1827 - val_root_mean_squared_error: 7435.5737\n",
      "Epoch 1516/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1795.6232 - root_mean_squared_error: 6896.2080 - val_loss: 1780.9760 - val_root_mean_squared_error: 7402.7461\n",
      "Epoch 1517/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1769.7935 - root_mean_squared_error: 6834.3867 - val_loss: 1763.7816 - val_root_mean_squared_error: 7671.6455\n",
      "Epoch 1518/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1796.2970 - root_mean_squared_error: 6956.9868 - val_loss: 1785.4392 - val_root_mean_squared_error: 7496.7915\n",
      "Epoch 1519/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1825.3264 - root_mean_squared_error: 6812.9775 - val_loss: 1761.2505 - val_root_mean_squared_error: 7296.5059\n",
      "Epoch 1520/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1785.9175 - root_mean_squared_error: 6814.0366 - val_loss: 1766.3833 - val_root_mean_squared_error: 7556.7290\n",
      "Epoch 1521/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1773.2977 - root_mean_squared_error: 6874.8354 - val_loss: 1771.5197 - val_root_mean_squared_error: 7528.8638\n",
      "Epoch 1522/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1777.2640 - root_mean_squared_error: 6881.2593 - val_loss: 1758.9891 - val_root_mean_squared_error: 7445.1089\n",
      "Epoch 1523/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1776.6404 - root_mean_squared_error: 6851.9482 - val_loss: 1768.7186 - val_root_mean_squared_error: 7427.2354\n",
      "Epoch 1524/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1781.6738 - root_mean_squared_error: 6822.3960 - val_loss: 1768.7754 - val_root_mean_squared_error: 7386.0342\n",
      "Epoch 1525/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1774.9124 - root_mean_squared_error: 6841.7402 - val_loss: 1749.3135 - val_root_mean_squared_error: 7455.4370\n",
      "Epoch 1526/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1775.3685 - root_mean_squared_error: 6878.7432 - val_loss: 1772.6530 - val_root_mean_squared_error: 7572.8535\n",
      "Epoch 1527/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1779.5488 - root_mean_squared_error: 6861.5332 - val_loss: 1758.4446 - val_root_mean_squared_error: 7469.3169\n",
      "Epoch 1528/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1776.8456 - root_mean_squared_error: 6839.0278 - val_loss: 1753.3119 - val_root_mean_squared_error: 7315.2041\n",
      "Epoch 1529/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1795.9814 - root_mean_squared_error: 6897.6948 - val_loss: 1762.1471 - val_root_mean_squared_error: 7436.8315\n",
      "Epoch 1530/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1804.7275 - root_mean_squared_error: 6777.9170 - val_loss: 1785.2953 - val_root_mean_squared_error: 7471.8574\n",
      "Epoch 1531/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1795.1583 - root_mean_squared_error: 6878.2554 - val_loss: 1760.5320 - val_root_mean_squared_error: 7593.9990\n",
      "Epoch 1532/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1782.6138 - root_mean_squared_error: 6834.1968 - val_loss: 1780.3667 - val_root_mean_squared_error: 7187.5586\n",
      "Epoch 1533/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1822.4015 - root_mean_squared_error: 6956.5576 - val_loss: 1766.0293 - val_root_mean_squared_error: 7461.8564\n",
      "Epoch 1534/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1799.3612 - root_mean_squared_error: 6772.4492 - val_loss: 1780.3912 - val_root_mean_squared_error: 7295.8560\n",
      "Epoch 1535/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1773.5640 - root_mean_squared_error: 6742.5977 - val_loss: 1757.0737 - val_root_mean_squared_error: 7567.6909\n",
      "Epoch 1536/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1797.5189 - root_mean_squared_error: 6784.4429 - val_loss: 1753.5815 - val_root_mean_squared_error: 7336.0225\n",
      "Epoch 1537/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1777.9373 - root_mean_squared_error: 6832.7939 - val_loss: 1759.0079 - val_root_mean_squared_error: 7391.6353\n",
      "Epoch 1538/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1782.1147 - root_mean_squared_error: 6856.3394 - val_loss: 1765.4503 - val_root_mean_squared_error: 7257.1899\n",
      "Epoch 1539/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1773.5553 - root_mean_squared_error: 6791.3271 - val_loss: 1753.0344 - val_root_mean_squared_error: 7507.7959\n",
      "Epoch 1540/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1771.9719 - root_mean_squared_error: 6852.9863 - val_loss: 1763.5444 - val_root_mean_squared_error: 7545.4561\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1541/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1769.3628 - root_mean_squared_error: 6822.1616 - val_loss: 1767.6887 - val_root_mean_squared_error: 7418.4526\n",
      "Epoch 1542/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1771.4137 - root_mean_squared_error: 6859.7578 - val_loss: 1748.1707 - val_root_mean_squared_error: 7402.3706\n",
      "Epoch 1543/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1784.6356 - root_mean_squared_error: 6813.2720 - val_loss: 1755.6482 - val_root_mean_squared_error: 7417.0869\n",
      "Epoch 1544/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1759.8744 - root_mean_squared_error: 6787.0166 - val_loss: 1743.1674 - val_root_mean_squared_error: 7559.4326\n",
      "Epoch 1545/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1773.1688 - root_mean_squared_error: 6865.0522 - val_loss: 1756.3125 - val_root_mean_squared_error: 7290.7139\n",
      "Epoch 1546/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1769.3069 - root_mean_squared_error: 6786.7983 - val_loss: 1746.8569 - val_root_mean_squared_error: 7288.2427\n",
      "Epoch 1547/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1769.1562 - root_mean_squared_error: 6805.6748 - val_loss: 1756.6913 - val_root_mean_squared_error: 7149.9897\n",
      "Epoch 1548/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1788.2224 - root_mean_squared_error: 6775.4346 - val_loss: 1727.6072 - val_root_mean_squared_error: 7138.5669\n",
      "Epoch 1549/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1790.9310 - root_mean_squared_error: 6938.5635 - val_loss: 1737.3159 - val_root_mean_squared_error: 7509.3569\n",
      "Epoch 1550/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1799.0109 - root_mean_squared_error: 6913.9370 - val_loss: 1748.0576 - val_root_mean_squared_error: 7299.4873\n",
      "Epoch 1551/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1776.5713 - root_mean_squared_error: 6814.7588 - val_loss: 1725.8383 - val_root_mean_squared_error: 7339.3818\n",
      "Epoch 1552/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1774.4866 - root_mean_squared_error: 6780.4834 - val_loss: 1738.5934 - val_root_mean_squared_error: 7208.9702\n",
      "Epoch 1553/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1776.1912 - root_mean_squared_error: 6838.2344 - val_loss: 1728.1873 - val_root_mean_squared_error: 7220.8154\n",
      "Epoch 1554/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1790.4264 - root_mean_squared_error: 6817.6421 - val_loss: 1743.9180 - val_root_mean_squared_error: 7232.4302\n",
      "Epoch 1555/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1775.2346 - root_mean_squared_error: 6864.1938 - val_loss: 1756.4940 - val_root_mean_squared_error: 7335.1519\n",
      "Epoch 1556/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1778.1790 - root_mean_squared_error: 6815.9185 - val_loss: 1744.7015 - val_root_mean_squared_error: 7185.7734\n",
      "Epoch 1557/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1770.0736 - root_mean_squared_error: 6748.4199 - val_loss: 1733.2788 - val_root_mean_squared_error: 7215.9717\n",
      "Epoch 1558/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1764.4277 - root_mean_squared_error: 6789.0854 - val_loss: 1722.4209 - val_root_mean_squared_error: 7282.6670\n",
      "Epoch 1559/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1781.3866 - root_mean_squared_error: 6814.4155 - val_loss: 1746.1755 - val_root_mean_squared_error: 7490.2251\n",
      "Epoch 1560/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1792.7286 - root_mean_squared_error: 6824.1851 - val_loss: 1716.0601 - val_root_mean_squared_error: 7236.7437\n",
      "Epoch 1561/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1788.2762 - root_mean_squared_error: 6806.4775 - val_loss: 1740.2887 - val_root_mean_squared_error: 7274.8926\n",
      "Epoch 1562/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1767.6329 - root_mean_squared_error: 6803.9014 - val_loss: 1725.3577 - val_root_mean_squared_error: 7217.7642\n",
      "Epoch 1563/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1781.1727 - root_mean_squared_error: 6837.9771 - val_loss: 1733.1434 - val_root_mean_squared_error: 7357.6787\n",
      "Epoch 1564/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1777.1292 - root_mean_squared_error: 6835.0190 - val_loss: 1736.5028 - val_root_mean_squared_error: 7150.9165\n",
      "Epoch 1565/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1794.4661 - root_mean_squared_error: 6815.3062 - val_loss: 1744.8821 - val_root_mean_squared_error: 6924.5767\n",
      "Epoch 1566/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1827.7350 - root_mean_squared_error: 6854.1406 - val_loss: 1728.3088 - val_root_mean_squared_error: 7072.5503\n",
      "Epoch 1567/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1774.1279 - root_mean_squared_error: 6784.2251 - val_loss: 1724.3915 - val_root_mean_squared_error: 7109.8535\n",
      "Epoch 1568/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1787.3882 - root_mean_squared_error: 6805.6064 - val_loss: 1729.4753 - val_root_mean_squared_error: 7251.7817\n",
      "Epoch 1569/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1795.4684 - root_mean_squared_error: 6761.2612 - val_loss: 1756.2065 - val_root_mean_squared_error: 7380.2690\n",
      "Epoch 1570/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1803.5912 - root_mean_squared_error: 6796.4053 - val_loss: 1716.3334 - val_root_mean_squared_error: 7068.7373\n",
      "Epoch 1571/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1776.5013 - root_mean_squared_error: 6854.8042 - val_loss: 1708.5204 - val_root_mean_squared_error: 7230.2212\n",
      "Epoch 1572/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1778.7338 - root_mean_squared_error: 6828.1367 - val_loss: 1741.9337 - val_root_mean_squared_error: 7455.6904\n",
      "Epoch 1573/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1808.3232 - root_mean_squared_error: 6932.5713 - val_loss: 1738.1754 - val_root_mean_squared_error: 7282.6782\n",
      "Epoch 1574/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1772.9243 - root_mean_squared_error: 6793.9272 - val_loss: 1720.5745 - val_root_mean_squared_error: 7107.4033\n",
      "Epoch 1575/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1783.8562 - root_mean_squared_error: 6982.6079 - val_loss: 1723.2317 - val_root_mean_squared_error: 7462.1621\n",
      "Epoch 1576/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1788.8024 - root_mean_squared_error: 6823.7905 - val_loss: 1749.4752 - val_root_mean_squared_error: 7198.7314\n",
      "Epoch 1577/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1761.6438 - root_mean_squared_error: 6762.3389 - val_loss: 1721.9397 - val_root_mean_squared_error: 7142.7422\n",
      "Epoch 1578/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1767.9757 - root_mean_squared_error: 6781.0649 - val_loss: 1731.0294 - val_root_mean_squared_error: 7237.5981\n",
      "Epoch 1579/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1763.1292 - root_mean_squared_error: 6761.3032 - val_loss: 1723.2676 - val_root_mean_squared_error: 6953.4639\n",
      "Epoch 1580/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1761.9604 - root_mean_squared_error: 6712.3135 - val_loss: 1720.1847 - val_root_mean_squared_error: 7081.8374\n",
      "Epoch 1581/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1796.2196 - root_mean_squared_error: 6805.3789 - val_loss: 1733.5250 - val_root_mean_squared_error: 7067.3794\n",
      "Epoch 1582/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1803.1647 - root_mean_squared_error: 6770.8618 - val_loss: 1741.4576 - val_root_mean_squared_error: 6990.1987\n",
      "Epoch 1583/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1774.9412 - root_mean_squared_error: 6769.0352 - val_loss: 1722.1842 - val_root_mean_squared_error: 7144.4189\n",
      "Epoch 1584/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1764.7314 - root_mean_squared_error: 6786.0054 - val_loss: 1713.3176 - val_root_mean_squared_error: 7222.6230\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1585/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1773.4121 - root_mean_squared_error: 6734.3818 - val_loss: 1735.2054 - val_root_mean_squared_error: 7132.2715\n",
      "Epoch 1586/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1767.5287 - root_mean_squared_error: 6790.9888 - val_loss: 1710.4130 - val_root_mean_squared_error: 6947.4277\n",
      "Epoch 1587/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1760.2708 - root_mean_squared_error: 6753.1001 - val_loss: 1725.4130 - val_root_mean_squared_error: 7219.3750\n",
      "Epoch 1588/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1796.0959 - root_mean_squared_error: 6829.3550 - val_loss: 1747.1041 - val_root_mean_squared_error: 7159.7549\n",
      "Epoch 1589/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1761.4083 - root_mean_squared_error: 6781.9009 - val_loss: 1719.2452 - val_root_mean_squared_error: 7003.8320\n",
      "Epoch 1590/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1769.7983 - root_mean_squared_error: 6754.5596 - val_loss: 1750.4948 - val_root_mean_squared_error: 7305.8193\n",
      "Epoch 1591/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1814.0029 - root_mean_squared_error: 6704.8745 - val_loss: 1755.8464 - val_root_mean_squared_error: 7038.6577\n",
      "Epoch 1592/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1785.2113 - root_mean_squared_error: 6758.7915 - val_loss: 1735.1124 - val_root_mean_squared_error: 7000.4492\n",
      "Epoch 1593/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1802.1292 - root_mean_squared_error: 6855.6772 - val_loss: 1726.1875 - val_root_mean_squared_error: 7025.5532\n",
      "Epoch 1594/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1770.6754 - root_mean_squared_error: 6736.6021 - val_loss: 1715.3914 - val_root_mean_squared_error: 7083.7310\n",
      "Epoch 1595/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1772.2014 - root_mean_squared_error: 6756.3096 - val_loss: 1718.9983 - val_root_mean_squared_error: 7134.2642\n",
      "Epoch 1596/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1765.0560 - root_mean_squared_error: 6803.6113 - val_loss: 1709.0280 - val_root_mean_squared_error: 7208.2544\n",
      "Epoch 1597/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1764.8629 - root_mean_squared_error: 6812.3848 - val_loss: 1709.4031 - val_root_mean_squared_error: 6967.5747\n",
      "Epoch 1598/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1756.2595 - root_mean_squared_error: 6795.3218 - val_loss: 1710.1542 - val_root_mean_squared_error: 7120.6689\n",
      "Epoch 1599/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1759.5873 - root_mean_squared_error: 6775.0342 - val_loss: 1707.0510 - val_root_mean_squared_error: 7075.8115\n",
      "Epoch 1600/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1755.3284 - root_mean_squared_error: 6758.2178 - val_loss: 1713.4752 - val_root_mean_squared_error: 7053.4609\n",
      "Epoch 1601/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1778.6190 - root_mean_squared_error: 6824.7988 - val_loss: 1718.0173 - val_root_mean_squared_error: 6878.1377\n",
      "Epoch 1602/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1801.0627 - root_mean_squared_error: 6868.2275 - val_loss: 1742.8868 - val_root_mean_squared_error: 6828.0801\n",
      "Epoch 1603/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1842.4393 - root_mean_squared_error: 6758.0840 - val_loss: 1712.4827 - val_root_mean_squared_error: 7220.1406\n",
      "Epoch 1604/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1777.5812 - root_mean_squared_error: 6737.9717 - val_loss: 1731.4447 - val_root_mean_squared_error: 7157.6797\n",
      "Epoch 1605/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1791.1212 - root_mean_squared_error: 6779.0044 - val_loss: 1724.9894 - val_root_mean_squared_error: 6992.1426\n",
      "Epoch 1606/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1769.0287 - root_mean_squared_error: 6724.5303 - val_loss: 1700.3131 - val_root_mean_squared_error: 6925.7603\n",
      "Epoch 1607/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1768.9440 - root_mean_squared_error: 6781.6655 - val_loss: 1713.6626 - val_root_mean_squared_error: 7003.9849\n",
      "Epoch 1608/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1757.2737 - root_mean_squared_error: 6754.0063 - val_loss: 1704.3922 - val_root_mean_squared_error: 7116.1055\n",
      "Epoch 1609/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1781.1294 - root_mean_squared_error: 6799.9844 - val_loss: 1690.0597 - val_root_mean_squared_error: 6845.2739\n",
      "Epoch 1610/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1765.0917 - root_mean_squared_error: 6707.4600 - val_loss: 1705.5227 - val_root_mean_squared_error: 7253.5645\n",
      "Epoch 1611/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1814.5732 - root_mean_squared_error: 6860.6055 - val_loss: 1702.9318 - val_root_mean_squared_error: 7116.9941\n",
      "Epoch 1612/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1782.2152 - root_mean_squared_error: 6744.5903 - val_loss: 1730.2037 - val_root_mean_squared_error: 6674.1484\n",
      "Epoch 1613/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1774.9093 - root_mean_squared_error: 6679.2759 - val_loss: 1673.9277 - val_root_mean_squared_error: 6973.1709\n",
      "Epoch 1614/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1763.2858 - root_mean_squared_error: 6761.2397 - val_loss: 1701.2570 - val_root_mean_squared_error: 7093.8369\n",
      "Epoch 1615/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1766.7446 - root_mean_squared_error: 6754.3564 - val_loss: 1693.5740 - val_root_mean_squared_error: 6892.3950\n",
      "Epoch 1616/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1751.9192 - root_mean_squared_error: 6743.9692 - val_loss: 1691.8936 - val_root_mean_squared_error: 7027.2988\n",
      "Epoch 1617/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1751.8661 - root_mean_squared_error: 6758.4829 - val_loss: 1695.5647 - val_root_mean_squared_error: 7117.9175\n",
      "Epoch 1618/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1772.2146 - root_mean_squared_error: 6814.1670 - val_loss: 1708.8214 - val_root_mean_squared_error: 6815.3530\n",
      "Epoch 1619/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1792.2277 - root_mean_squared_error: 6646.4902 - val_loss: 1730.5533 - val_root_mean_squared_error: 6568.4946\n",
      "Epoch 1620/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1799.0889 - root_mean_squared_error: 6772.6631 - val_loss: 1689.3330 - val_root_mean_squared_error: 6900.5933\n",
      "Epoch 1621/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1786.5829 - root_mean_squared_error: 6673.7559 - val_loss: 1732.2916 - val_root_mean_squared_error: 6985.4009\n",
      "Epoch 1622/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1793.6257 - root_mean_squared_error: 6750.3442 - val_loss: 1679.3242 - val_root_mean_squared_error: 6812.4995\n",
      "Epoch 1623/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1764.1333 - root_mean_squared_error: 6700.4727 - val_loss: 1684.1605 - val_root_mean_squared_error: 6921.3096\n",
      "Epoch 1624/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1772.0303 - root_mean_squared_error: 6726.8716 - val_loss: 1718.2181 - val_root_mean_squared_error: 6924.3970\n",
      "Epoch 1625/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1784.2417 - root_mean_squared_error: 6771.4316 - val_loss: 1701.2161 - val_root_mean_squared_error: 6929.3594\n",
      "Epoch 1626/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1747.3961 - root_mean_squared_error: 6704.6089 - val_loss: 1679.9412 - val_root_mean_squared_error: 6650.2573\n",
      "Epoch 1627/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1777.9688 - root_mean_squared_error: 6718.8506 - val_loss: 1681.1461 - val_root_mean_squared_error: 6540.5371\n",
      "Epoch 1628/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1791.0292 - root_mean_squared_error: 6697.3345 - val_loss: 1686.8755 - val_root_mean_squared_error: 6879.2383\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1629/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1766.4287 - root_mean_squared_error: 6747.3730 - val_loss: 1710.8799 - val_root_mean_squared_error: 7317.3438\n",
      "Epoch 1630/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1789.3639 - root_mean_squared_error: 6784.5830 - val_loss: 1688.2554 - val_root_mean_squared_error: 7047.9331\n",
      "Epoch 1631/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1753.4639 - root_mean_squared_error: 6747.0015 - val_loss: 1684.3961 - val_root_mean_squared_error: 6749.1768\n",
      "Epoch 1632/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1749.3904 - root_mean_squared_error: 6672.7734 - val_loss: 1666.6512 - val_root_mean_squared_error: 6767.7310\n",
      "Epoch 1633/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1749.3586 - root_mean_squared_error: 6753.9204 - val_loss: 1684.6174 - val_root_mean_squared_error: 6758.9497\n",
      "Epoch 1634/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1760.4744 - root_mean_squared_error: 6718.3169 - val_loss: 1680.6006 - val_root_mean_squared_error: 6678.1855\n",
      "Epoch 1635/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1761.8578 - root_mean_squared_error: 6662.9019 - val_loss: 1656.5565 - val_root_mean_squared_error: 6714.5283\n",
      "Epoch 1636/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1762.7151 - root_mean_squared_error: 6703.4453 - val_loss: 1692.2935 - val_root_mean_squared_error: 6951.5137\n",
      "Epoch 1637/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1759.2596 - root_mean_squared_error: 6672.1436 - val_loss: 1681.8425 - val_root_mean_squared_error: 6553.4868\n",
      "Epoch 1638/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1775.2637 - root_mean_squared_error: 6657.5210 - val_loss: 1693.4733 - val_root_mean_squared_error: 6753.8042\n",
      "Epoch 1639/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1780.9680 - root_mean_squared_error: 6815.4648 - val_loss: 1692.1292 - val_root_mean_squared_error: 6956.5674\n",
      "Epoch 1640/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1766.7427 - root_mean_squared_error: 6710.3325 - val_loss: 1678.0380 - val_root_mean_squared_error: 6574.8145\n",
      "Epoch 1641/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1790.6353 - root_mean_squared_error: 6673.0195 - val_loss: 1666.5175 - val_root_mean_squared_error: 6805.3672\n",
      "Epoch 1642/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1754.4767 - root_mean_squared_error: 6635.1240 - val_loss: 1679.1738 - val_root_mean_squared_error: 7025.5757\n",
      "Epoch 1643/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1769.5806 - root_mean_squared_error: 6768.7031 - val_loss: 1703.3080 - val_root_mean_squared_error: 6826.7944\n",
      "Epoch 1644/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1767.9548 - root_mean_squared_error: 6742.8853 - val_loss: 1709.2312 - val_root_mean_squared_error: 6480.2759\n",
      "Epoch 1645/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1780.1525 - root_mean_squared_error: 6592.8955 - val_loss: 1697.0000 - val_root_mean_squared_error: 6619.0391\n",
      "Epoch 1646/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1757.3193 - root_mean_squared_error: 6646.6528 - val_loss: 1676.0072 - val_root_mean_squared_error: 6983.0703\n",
      "Epoch 1647/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1775.9917 - root_mean_squared_error: 6782.3296 - val_loss: 1699.5857 - val_root_mean_squared_error: 6727.9668\n",
      "Epoch 1648/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1803.2842 - root_mean_squared_error: 6810.0674 - val_loss: 1706.8130 - val_root_mean_squared_error: 6770.4468\n",
      "Epoch 1649/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1801.3112 - root_mean_squared_error: 6690.0176 - val_loss: 1684.2510 - val_root_mean_squared_error: 6904.3613\n",
      "Epoch 1650/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1771.7295 - root_mean_squared_error: 6715.0156 - val_loss: 1685.5427 - val_root_mean_squared_error: 7074.1045\n",
      "Epoch 1651/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1774.8475 - root_mean_squared_error: 6771.1445 - val_loss: 1702.9347 - val_root_mean_squared_error: 6991.4077\n",
      "Epoch 1652/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1759.0493 - root_mean_squared_error: 6682.5903 - val_loss: 1674.2999 - val_root_mean_squared_error: 6808.9521\n",
      "Epoch 1653/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1746.6572 - root_mean_squared_error: 6701.7632 - val_loss: 1677.2124 - val_root_mean_squared_error: 6800.6436\n",
      "Epoch 1654/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1767.9088 - root_mean_squared_error: 6769.1147 - val_loss: 1678.5475 - val_root_mean_squared_error: 6804.2695\n",
      "Epoch 1655/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1748.1609 - root_mean_squared_error: 6690.8569 - val_loss: 1682.6642 - val_root_mean_squared_error: 6580.7461\n",
      "Epoch 1656/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1782.0109 - root_mean_squared_error: 6709.3545 - val_loss: 1651.2712 - val_root_mean_squared_error: 6657.0771\n",
      "Epoch 1657/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1800.3225 - root_mean_squared_error: 6818.3066 - val_loss: 1663.6334 - val_root_mean_squared_error: 6653.8027\n",
      "Epoch 1658/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1771.8831 - root_mean_squared_error: 6611.0010 - val_loss: 1694.8813 - val_root_mean_squared_error: 6727.0942\n",
      "Epoch 1659/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1759.8622 - root_mean_squared_error: 6668.5176 - val_loss: 1658.4097 - val_root_mean_squared_error: 7039.8276\n",
      "Epoch 1660/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1809.8505 - root_mean_squared_error: 6829.8218 - val_loss: 1711.9386 - val_root_mean_squared_error: 6865.5708\n",
      "Epoch 1661/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1769.5739 - root_mean_squared_error: 6717.5483 - val_loss: 1673.5988 - val_root_mean_squared_error: 6670.0649\n",
      "Epoch 1662/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1766.3862 - root_mean_squared_error: 6662.6831 - val_loss: 1661.2412 - val_root_mean_squared_error: 6316.8633\n",
      "Epoch 1663/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1767.5616 - root_mean_squared_error: 6602.6816 - val_loss: 1660.2369 - val_root_mean_squared_error: 6586.8228\n",
      "Epoch 1664/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1749.2443 - root_mean_squared_error: 6682.5996 - val_loss: 1656.7030 - val_root_mean_squared_error: 6896.4814\n",
      "Epoch 1665/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1748.0237 - root_mean_squared_error: 6692.7896 - val_loss: 1662.3383 - val_root_mean_squared_error: 6704.7373\n",
      "Epoch 1666/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1743.5276 - root_mean_squared_error: 6672.4077 - val_loss: 1651.6399 - val_root_mean_squared_error: 6539.2358\n",
      "Epoch 1667/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1753.0646 - root_mean_squared_error: 6678.3462 - val_loss: 1651.9580 - val_root_mean_squared_error: 6691.9097\n",
      "Epoch 1668/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1745.8527 - root_mean_squared_error: 6675.7661 - val_loss: 1668.6180 - val_root_mean_squared_error: 6572.8491\n",
      "Epoch 1669/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1760.1398 - root_mean_squared_error: 6662.1045 - val_loss: 1684.2650 - val_root_mean_squared_error: 6253.8906\n",
      "Epoch 1670/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1826.5498 - root_mean_squared_error: 6762.0034 - val_loss: 1675.7592 - val_root_mean_squared_error: 6594.3345\n",
      "Epoch 1671/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1797.9265 - root_mean_squared_error: 6790.9639 - val_loss: 1678.1564 - val_root_mean_squared_error: 6727.9331\n",
      "Epoch 1672/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1756.7596 - root_mean_squared_error: 6589.2930 - val_loss: 1684.2361 - val_root_mean_squared_error: 6816.4424\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1673/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1754.5115 - root_mean_squared_error: 6651.1904 - val_loss: 1661.2883 - val_root_mean_squared_error: 6522.1079\n",
      "Epoch 1674/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1752.4534 - root_mean_squared_error: 6617.4023 - val_loss: 1650.5825 - val_root_mean_squared_error: 6512.7344\n",
      "Epoch 1675/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1745.7078 - root_mean_squared_error: 6656.5996 - val_loss: 1658.0884 - val_root_mean_squared_error: 6489.2446\n",
      "Epoch 1676/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1758.3572 - root_mean_squared_error: 6670.8589 - val_loss: 1655.2849 - val_root_mean_squared_error: 6644.6743\n",
      "Epoch 1677/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1734.4000 - root_mean_squared_error: 6646.8330 - val_loss: 1642.7170 - val_root_mean_squared_error: 6524.4517\n",
      "Epoch 1678/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1729.9556 - root_mean_squared_error: 6651.7202 - val_loss: 1652.5159 - val_root_mean_squared_error: 6678.0601\n",
      "Epoch 1679/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1733.6315 - root_mean_squared_error: 6640.3862 - val_loss: 1657.2305 - val_root_mean_squared_error: 6437.0039\n",
      "Epoch 1680/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1745.1414 - root_mean_squared_error: 6560.4272 - val_loss: 1667.8910 - val_root_mean_squared_error: 6698.6030\n",
      "Epoch 1681/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1825.2682 - root_mean_squared_error: 6741.4214 - val_loss: 1670.7382 - val_root_mean_squared_error: 6277.4658\n",
      "Epoch 1682/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1785.4873 - root_mean_squared_error: 6562.0542 - val_loss: 1694.7134 - val_root_mean_squared_error: 6201.8101\n",
      "Epoch 1683/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1792.2634 - root_mean_squared_error: 6651.8408 - val_loss: 1630.0240 - val_root_mean_squared_error: 6620.4839\n",
      "Epoch 1684/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1783.8561 - root_mean_squared_error: 6614.4507 - val_loss: 1655.0620 - val_root_mean_squared_error: 6596.5693\n",
      "Epoch 1685/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1762.4933 - root_mean_squared_error: 6642.9507 - val_loss: 1655.3213 - val_root_mean_squared_error: 6655.7456\n",
      "Epoch 1686/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1758.9926 - root_mean_squared_error: 6654.4517 - val_loss: 1667.2997 - val_root_mean_squared_error: 6621.5479\n",
      "Epoch 1687/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1750.7264 - root_mean_squared_error: 6621.4546 - val_loss: 1657.3008 - val_root_mean_squared_error: 6470.3115\n",
      "Epoch 1688/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1747.0115 - root_mean_squared_error: 6605.2329 - val_loss: 1629.8043 - val_root_mean_squared_error: 6235.7715\n",
      "Epoch 1689/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1768.1716 - root_mean_squared_error: 6564.5859 - val_loss: 1622.4601 - val_root_mean_squared_error: 6358.7178\n",
      "Epoch 1690/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1775.8965 - root_mean_squared_error: 6787.6748 - val_loss: 1655.0541 - val_root_mean_squared_error: 6880.2554\n",
      "Epoch 1691/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.1823 - root_mean_squared_error: 6658.3530 - val_loss: 1674.1556 - val_root_mean_squared_error: 6511.1167\n",
      "Epoch 1692/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1733.8174 - root_mean_squared_error: 6579.9775 - val_loss: 1641.4886 - val_root_mean_squared_error: 6534.1797\n",
      "Epoch 1693/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1744.2631 - root_mean_squared_error: 6635.5840 - val_loss: 1646.8002 - val_root_mean_squared_error: 6358.7334\n",
      "Epoch 1694/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1731.4629 - root_mean_squared_error: 6568.9429 - val_loss: 1633.5345 - val_root_mean_squared_error: 6240.4731\n",
      "Epoch 1695/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1749.2040 - root_mean_squared_error: 6593.8501 - val_loss: 1630.1357 - val_root_mean_squared_error: 6263.6831\n",
      "Epoch 1696/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1749.2026 - root_mean_squared_error: 6580.9341 - val_loss: 1641.8191 - val_root_mean_squared_error: 6640.3447\n",
      "Epoch 1697/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1747.9449 - root_mean_squared_error: 6640.1099 - val_loss: 1653.4247 - val_root_mean_squared_error: 6297.1284\n",
      "Epoch 1698/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1756.0022 - root_mean_squared_error: 6681.8525 - val_loss: 1647.5485 - val_root_mean_squared_error: 6426.3569\n",
      "Epoch 1699/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1770.6562 - root_mean_squared_error: 6703.6807 - val_loss: 1652.5842 - val_root_mean_squared_error: 6425.3423\n",
      "Epoch 1700/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1741.0886 - root_mean_squared_error: 6527.0801 - val_loss: 1644.1522 - val_root_mean_squared_error: 6606.3423\n",
      "Epoch 1701/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1760.6410 - root_mean_squared_error: 6632.8193 - val_loss: 1648.8551 - val_root_mean_squared_error: 6492.9150\n",
      "Epoch 1702/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1741.3246 - root_mean_squared_error: 6604.9961 - val_loss: 1653.7405 - val_root_mean_squared_error: 6591.4131\n",
      "Epoch 1703/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1765.3481 - root_mean_squared_error: 6648.7319 - val_loss: 1665.0363 - val_root_mean_squared_error: 6515.9355\n",
      "Epoch 1704/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1768.2318 - root_mean_squared_error: 6688.8657 - val_loss: 1664.4062 - val_root_mean_squared_error: 6443.3374\n",
      "Epoch 1705/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1749.8231 - root_mean_squared_error: 6599.2329 - val_loss: 1649.6300 - val_root_mean_squared_error: 6366.5537\n",
      "Epoch 1706/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1742.0958 - root_mean_squared_error: 6508.2539 - val_loss: 1642.1965 - val_root_mean_squared_error: 5837.9282\n",
      "Epoch 1707/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1772.1765 - root_mean_squared_error: 6486.5776 - val_loss: 1600.4192 - val_root_mean_squared_error: 6358.2539\n",
      "Epoch 1708/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1779.5073 - root_mean_squared_error: 6600.9282 - val_loss: 1644.0198 - val_root_mean_squared_error: 6449.5923\n",
      "Epoch 1709/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1756.9248 - root_mean_squared_error: 6614.5347 - val_loss: 1634.8081 - val_root_mean_squared_error: 6400.6328\n",
      "Epoch 1710/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1749.6995 - root_mean_squared_error: 6626.7451 - val_loss: 1647.4316 - val_root_mean_squared_error: 6042.2319\n",
      "Epoch 1711/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1785.3334 - root_mean_squared_error: 6574.3794 - val_loss: 1625.2317 - val_root_mean_squared_error: 6387.3662\n",
      "Epoch 1712/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1767.9297 - root_mean_squared_error: 6553.5181 - val_loss: 1658.6523 - val_root_mean_squared_error: 6531.4873\n",
      "Epoch 1713/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1797.0259 - root_mean_squared_error: 6566.5229 - val_loss: 1628.0325 - val_root_mean_squared_error: 6522.0923\n",
      "Epoch 1714/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1796.1813 - root_mean_squared_error: 6706.9756 - val_loss: 1605.8621 - val_root_mean_squared_error: 6245.0757\n",
      "Epoch 1715/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1723.8094 - root_mean_squared_error: 6557.6289 - val_loss: 1614.5892 - val_root_mean_squared_error: 6035.5562\n",
      "Epoch 1716/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1743.8645 - root_mean_squared_error: 6530.4194 - val_loss: 1611.9014 - val_root_mean_squared_error: 6239.9888\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1717/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1738.2068 - root_mean_squared_error: 6620.7451 - val_loss: 1624.3828 - val_root_mean_squared_error: 6351.2397\n",
      "Epoch 1718/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1732.8138 - root_mean_squared_error: 6608.3228 - val_loss: 1628.8706 - val_root_mean_squared_error: 6332.0830\n",
      "Epoch 1719/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1745.7528 - root_mean_squared_error: 6613.0684 - val_loss: 1623.1234 - val_root_mean_squared_error: 6239.7466\n",
      "Epoch 1720/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1765.1304 - root_mean_squared_error: 6469.7061 - val_loss: 1646.0780 - val_root_mean_squared_error: 6301.1016\n",
      "Epoch 1721/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1777.1074 - root_mean_squared_error: 6516.8525 - val_loss: 1628.2095 - val_root_mean_squared_error: 6233.4736\n",
      "Epoch 1722/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1738.7295 - root_mean_squared_error: 6512.2427 - val_loss: 1621.5950 - val_root_mean_squared_error: 6021.2725\n",
      "Epoch 1723/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1747.5892 - root_mean_squared_error: 6543.1733 - val_loss: 1618.8920 - val_root_mean_squared_error: 6303.8892\n",
      "Epoch 1724/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1759.3392 - root_mean_squared_error: 6621.8984 - val_loss: 1648.4918 - val_root_mean_squared_error: 6252.9336\n",
      "Epoch 1725/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1788.5505 - root_mean_squared_error: 6623.9785 - val_loss: 1611.4369 - val_root_mean_squared_error: 6273.9399\n",
      "Epoch 1726/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1761.0840 - root_mean_squared_error: 6558.1367 - val_loss: 1619.8295 - val_root_mean_squared_error: 6044.0654\n",
      "Epoch 1727/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1734.1975 - root_mean_squared_error: 6570.3276 - val_loss: 1612.0439 - val_root_mean_squared_error: 6278.4556\n",
      "Epoch 1728/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1734.3407 - root_mean_squared_error: 6585.3467 - val_loss: 1619.6669 - val_root_mean_squared_error: 6378.3384\n",
      "Epoch 1729/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1730.8009 - root_mean_squared_error: 6569.2710 - val_loss: 1609.1915 - val_root_mean_squared_error: 6093.6890\n",
      "Epoch 1730/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1730.8689 - root_mean_squared_error: 6507.0171 - val_loss: 1601.5300 - val_root_mean_squared_error: 6137.0796\n",
      "Epoch 1731/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1765.0793 - root_mean_squared_error: 6587.4805 - val_loss: 1641.6356 - val_root_mean_squared_error: 6123.0610\n",
      "Epoch 1732/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1810.8193 - root_mean_squared_error: 6520.8457 - val_loss: 1621.2260 - val_root_mean_squared_error: 6059.5728\n",
      "Epoch 1733/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1752.2260 - root_mean_squared_error: 6559.5029 - val_loss: 1600.8339 - val_root_mean_squared_error: 6265.6777\n",
      "Epoch 1734/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1733.2305 - root_mean_squared_error: 6549.3433 - val_loss: 1615.9412 - val_root_mean_squared_error: 6189.5415\n",
      "Epoch 1735/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1733.8641 - root_mean_squared_error: 6550.9624 - val_loss: 1583.2115 - val_root_mean_squared_error: 5779.4580\n",
      "Epoch 1736/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1745.9275 - root_mean_squared_error: 6540.6543 - val_loss: 1592.6183 - val_root_mean_squared_error: 6072.3252\n",
      "Epoch 1737/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1725.1956 - root_mean_squared_error: 6531.8823 - val_loss: 1601.8960 - val_root_mean_squared_error: 6131.7334\n",
      "Epoch 1738/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1742.9425 - root_mean_squared_error: 6606.9653 - val_loss: 1591.9053 - val_root_mean_squared_error: 6230.7988\n",
      "Epoch 1739/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1718.2482 - root_mean_squared_error: 6500.7891 - val_loss: 1623.7141 - val_root_mean_squared_error: 6169.4014\n",
      "Epoch 1740/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1730.2164 - root_mean_squared_error: 6524.2451 - val_loss: 1612.0719 - val_root_mean_squared_error: 6010.8809\n",
      "Epoch 1741/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1723.1528 - root_mean_squared_error: 6508.8999 - val_loss: 1593.9584 - val_root_mean_squared_error: 6007.3877\n",
      "Epoch 1742/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1729.8510 - root_mean_squared_error: 6528.3794 - val_loss: 1597.3828 - val_root_mean_squared_error: 5967.2446\n",
      "Epoch 1743/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1730.0908 - root_mean_squared_error: 6537.7930 - val_loss: 1573.6160 - val_root_mean_squared_error: 6134.7783\n",
      "Epoch 1744/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1743.1171 - root_mean_squared_error: 6648.5532 - val_loss: 1609.2815 - val_root_mean_squared_error: 6233.1187\n",
      "Epoch 1745/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1732.4635 - root_mean_squared_error: 6511.7666 - val_loss: 1620.5862 - val_root_mean_squared_error: 6041.1514\n",
      "Epoch 1746/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1724.3602 - root_mean_squared_error: 6532.5723 - val_loss: 1587.1448 - val_root_mean_squared_error: 5867.6465\n",
      "Epoch 1747/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1728.2615 - root_mean_squared_error: 6532.0649 - val_loss: 1582.7206 - val_root_mean_squared_error: 5924.0444\n",
      "Epoch 1748/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1734.9862 - root_mean_squared_error: 6590.0532 - val_loss: 1592.3060 - val_root_mean_squared_error: 6283.3442\n",
      "Epoch 1749/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1735.7804 - root_mean_squared_error: 6571.4004 - val_loss: 1606.3811 - val_root_mean_squared_error: 6119.4951\n",
      "Epoch 1750/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1721.0089 - root_mean_squared_error: 6549.5117 - val_loss: 1581.1744 - val_root_mean_squared_error: 6217.2476\n",
      "Epoch 1751/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1788.7935 - root_mean_squared_error: 6640.2803 - val_loss: 1607.6913 - val_root_mean_squared_error: 6238.6782\n",
      "Epoch 1752/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1758.2817 - root_mean_squared_error: 6580.1895 - val_loss: 1614.2173 - val_root_mean_squared_error: 5987.6558\n",
      "Epoch 1753/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1734.1135 - root_mean_squared_error: 6560.2075 - val_loss: 1601.5356 - val_root_mean_squared_error: 5517.5298\n",
      "Epoch 1754/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1766.1481 - root_mean_squared_error: 6427.5015 - val_loss: 1563.5552 - val_root_mean_squared_error: 5919.0508\n",
      "Epoch 1755/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1717.9498 - root_mean_squared_error: 6496.1738 - val_loss: 1590.4364 - val_root_mean_squared_error: 5987.7427\n",
      "Epoch 1756/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1724.1033 - root_mean_squared_error: 6526.4272 - val_loss: 1593.4116 - val_root_mean_squared_error: 6170.6592\n",
      "Epoch 1757/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.9070 - root_mean_squared_error: 6568.7837 - val_loss: 1596.8341 - val_root_mean_squared_error: 5561.0308\n",
      "Epoch 1758/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1745.3918 - root_mean_squared_error: 6462.9800 - val_loss: 1567.3794 - val_root_mean_squared_error: 5722.0542\n",
      "Epoch 1759/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1720.2646 - root_mean_squared_error: 6546.2900 - val_loss: 1565.2977 - val_root_mean_squared_error: 5853.0884\n",
      "Epoch 1760/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1715.0841 - root_mean_squared_error: 6528.5483 - val_loss: 1563.9681 - val_root_mean_squared_error: 5977.9199\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1761/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.2394 - root_mean_squared_error: 6501.9912 - val_loss: 1589.8918 - val_root_mean_squared_error: 5886.8921\n",
      "Epoch 1762/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1742.1509 - root_mean_squared_error: 6470.0435 - val_loss: 1618.5566 - val_root_mean_squared_error: 5943.1470\n",
      "Epoch 1763/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1799.7627 - root_mean_squared_error: 6484.1914 - val_loss: 1622.4062 - val_root_mean_squared_error: 5977.4009\n",
      "Epoch 1764/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1770.9993 - root_mean_squared_error: 6460.3711 - val_loss: 1568.5701 - val_root_mean_squared_error: 5684.4141\n",
      "Epoch 1765/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.9150 - root_mean_squared_error: 6478.1533 - val_loss: 1595.7417 - val_root_mean_squared_error: 5795.5923\n",
      "Epoch 1766/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1734.5236 - root_mean_squared_error: 6501.4849 - val_loss: 1604.1282 - val_root_mean_squared_error: 5727.4072\n",
      "Epoch 1767/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1743.0681 - root_mean_squared_error: 6492.2974 - val_loss: 1578.6155 - val_root_mean_squared_error: 5745.5908\n",
      "Epoch 1768/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.9910 - root_mean_squared_error: 6434.3296 - val_loss: 1583.8098 - val_root_mean_squared_error: 5960.5469\n",
      "Epoch 1769/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1745.9966 - root_mean_squared_error: 6538.4551 - val_loss: 1619.4343 - val_root_mean_squared_error: 6239.7319\n",
      "Epoch 1770/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1766.0265 - root_mean_squared_error: 6512.7461 - val_loss: 1608.9435 - val_root_mean_squared_error: 5996.3701\n",
      "Epoch 1771/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1731.1230 - root_mean_squared_error: 6453.3750 - val_loss: 1593.8378 - val_root_mean_squared_error: 5654.3286\n",
      "Epoch 1772/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1724.1511 - root_mean_squared_error: 6462.0132 - val_loss: 1571.3306 - val_root_mean_squared_error: 5773.8589\n",
      "Epoch 1773/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1723.7885 - root_mean_squared_error: 6434.3247 - val_loss: 1568.9291 - val_root_mean_squared_error: 5636.6777\n",
      "Epoch 1774/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1719.3335 - root_mean_squared_error: 6424.3247 - val_loss: 1563.3221 - val_root_mean_squared_error: 5561.2300\n",
      "Epoch 1775/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1717.4751 - root_mean_squared_error: 6457.8086 - val_loss: 1550.7251 - val_root_mean_squared_error: 5796.7617\n",
      "Epoch 1776/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1740.7950 - root_mean_squared_error: 6472.8706 - val_loss: 1578.2830 - val_root_mean_squared_error: 5715.0537\n",
      "Epoch 1777/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1747.4728 - root_mean_squared_error: 6603.6807 - val_loss: 1587.6333 - val_root_mean_squared_error: 5806.7188\n",
      "Epoch 1778/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1737.2111 - root_mean_squared_error: 6459.2134 - val_loss: 1573.4650 - val_root_mean_squared_error: 5723.9673\n",
      "Epoch 1779/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1720.2640 - root_mean_squared_error: 6492.0361 - val_loss: 1572.6984 - val_root_mean_squared_error: 5803.6333\n",
      "Epoch 1780/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1714.3420 - root_mean_squared_error: 6480.6338 - val_loss: 1570.6038 - val_root_mean_squared_error: 5750.2168\n",
      "Epoch 1781/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1730.3092 - root_mean_squared_error: 6545.0776 - val_loss: 1598.0562 - val_root_mean_squared_error: 5706.0107\n",
      "Epoch 1782/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1734.1284 - root_mean_squared_error: 6538.0215 - val_loss: 1577.3093 - val_root_mean_squared_error: 5749.7642\n",
      "Epoch 1783/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1749.0854 - root_mean_squared_error: 6479.3618 - val_loss: 1566.0909 - val_root_mean_squared_error: 5617.5986\n",
      "Epoch 1784/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1736.4268 - root_mean_squared_error: 6483.1196 - val_loss: 1543.2810 - val_root_mean_squared_error: 5552.5693\n",
      "Epoch 1785/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.0166 - root_mean_squared_error: 6506.4663 - val_loss: 1581.2526 - val_root_mean_squared_error: 5584.9194\n",
      "Epoch 1786/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1747.6515 - root_mean_squared_error: 6498.1284 - val_loss: 1584.7880 - val_root_mean_squared_error: 5806.5112\n",
      "Epoch 1787/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1775.5215 - root_mean_squared_error: 6595.3003 - val_loss: 1574.3979 - val_root_mean_squared_error: 5769.5327\n",
      "Epoch 1788/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1752.8405 - root_mean_squared_error: 6412.6455 - val_loss: 1594.1349 - val_root_mean_squared_error: 5695.1328\n",
      "Epoch 1789/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1739.4830 - root_mean_squared_error: 6445.0273 - val_loss: 1554.3507 - val_root_mean_squared_error: 5687.8696\n",
      "Epoch 1790/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1725.1752 - root_mean_squared_error: 6462.3179 - val_loss: 1551.7222 - val_root_mean_squared_error: 5696.2832\n",
      "Epoch 1791/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1729.1823 - root_mean_squared_error: 6525.6914 - val_loss: 1559.6862 - val_root_mean_squared_error: 5750.1826\n",
      "Epoch 1792/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1735.7870 - root_mean_squared_error: 6455.8716 - val_loss: 1618.2944 - val_root_mean_squared_error: 5724.1387\n",
      "Epoch 1793/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1741.2113 - root_mean_squared_error: 6477.7974 - val_loss: 1553.0874 - val_root_mean_squared_error: 5249.6377\n",
      "Epoch 1794/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1775.9390 - root_mean_squared_error: 6499.3706 - val_loss: 1568.7731 - val_root_mean_squared_error: 5549.2988\n",
      "Epoch 1795/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1760.6704 - root_mean_squared_error: 6512.5317 - val_loss: 1575.1970 - val_root_mean_squared_error: 5961.1846\n",
      "Epoch 1796/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1747.9512 - root_mean_squared_error: 6515.1758 - val_loss: 1578.7942 - val_root_mean_squared_error: 5768.7876\n",
      "Epoch 1797/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1723.2158 - root_mean_squared_error: 6468.8828 - val_loss: 1565.9718 - val_root_mean_squared_error: 5509.1240\n",
      "Epoch 1798/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1719.6998 - root_mean_squared_error: 6451.7031 - val_loss: 1545.3000 - val_root_mean_squared_error: 5592.9678\n",
      "Epoch 1799/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1715.7384 - root_mean_squared_error: 6445.9399 - val_loss: 1555.7611 - val_root_mean_squared_error: 5608.6035\n",
      "Epoch 1800/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1712.9850 - root_mean_squared_error: 6460.6729 - val_loss: 1535.2374 - val_root_mean_squared_error: 5348.7358\n",
      "Epoch 1801/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1729.5764 - root_mean_squared_error: 6412.2251 - val_loss: 1514.7832 - val_root_mean_squared_error: 5181.6748\n",
      "Epoch 1802/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1722.1687 - root_mean_squared_error: 6471.4253 - val_loss: 1542.7415 - val_root_mean_squared_error: 5565.1191\n",
      "Epoch 1803/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.7277 - root_mean_squared_error: 6420.8608 - val_loss: 1599.3252 - val_root_mean_squared_error: 5362.0938\n",
      "Epoch 1804/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1754.9775 - root_mean_squared_error: 6440.3159 - val_loss: 1516.5229 - val_root_mean_squared_error: 5686.4712\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1805/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1743.5796 - root_mean_squared_error: 6507.3608 - val_loss: 1532.8202 - val_root_mean_squared_error: 5333.9883\n",
      "Epoch 1806/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1721.1727 - root_mean_squared_error: 6409.0444 - val_loss: 1522.7161 - val_root_mean_squared_error: 5532.6899\n",
      "Epoch 1807/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1712.8788 - root_mean_squared_error: 6463.6606 - val_loss: 1605.1591 - val_root_mean_squared_error: 5377.7573\n",
      "Epoch 1808/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1731.4792 - root_mean_squared_error: 6439.8291 - val_loss: 1526.8171 - val_root_mean_squared_error: 5450.6333\n",
      "Epoch 1809/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1709.5160 - root_mean_squared_error: 6428.1245 - val_loss: 1543.5509 - val_root_mean_squared_error: 5404.9141\n",
      "Epoch 1810/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1711.9283 - root_mean_squared_error: 6417.3232 - val_loss: 1520.9728 - val_root_mean_squared_error: 5312.0269\n",
      "Epoch 1811/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1717.2937 - root_mean_squared_error: 6511.5884 - val_loss: 1540.6161 - val_root_mean_squared_error: 5330.4805\n",
      "Epoch 1812/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1745.1611 - root_mean_squared_error: 6348.0049 - val_loss: 1560.8754 - val_root_mean_squared_error: 5536.0205\n",
      "Epoch 1813/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1733.3278 - root_mean_squared_error: 6452.9238 - val_loss: 1573.2341 - val_root_mean_squared_error: 5400.9751\n",
      "Epoch 1814/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1730.6829 - root_mean_squared_error: 6403.9829 - val_loss: 1537.2463 - val_root_mean_squared_error: 5248.4126\n",
      "Epoch 1815/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1712.7461 - root_mean_squared_error: 6404.4883 - val_loss: 1553.6334 - val_root_mean_squared_error: 5166.3018\n",
      "Epoch 1816/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1763.1500 - root_mean_squared_error: 6362.6211 - val_loss: 1545.0084 - val_root_mean_squared_error: 5350.5591\n",
      "Epoch 1817/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1720.4078 - root_mean_squared_error: 6396.9922 - val_loss: 1533.5540 - val_root_mean_squared_error: 5363.6348\n",
      "Epoch 1818/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1713.5099 - root_mean_squared_error: 6391.7617 - val_loss: 1528.9932 - val_root_mean_squared_error: 5323.7642\n",
      "Epoch 1819/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1721.0829 - root_mean_squared_error: 6384.6323 - val_loss: 1499.0002 - val_root_mean_squared_error: 5295.2900\n",
      "Epoch 1820/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1734.2461 - root_mean_squared_error: 6394.7432 - val_loss: 1551.8370 - val_root_mean_squared_error: 5604.0767\n",
      "Epoch 1821/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1807.7030 - root_mean_squared_error: 6522.0229 - val_loss: 1536.9630 - val_root_mean_squared_error: 5152.9185\n",
      "Epoch 1822/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.4850 - root_mean_squared_error: 6379.8843 - val_loss: 1512.1271 - val_root_mean_squared_error: 5220.7349\n",
      "Epoch 1823/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1726.5844 - root_mean_squared_error: 6418.6289 - val_loss: 1517.8403 - val_root_mean_squared_error: 5281.1294\n",
      "Epoch 1824/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1716.1368 - root_mean_squared_error: 6448.3320 - val_loss: 1526.4291 - val_root_mean_squared_error: 5560.5112\n",
      "Epoch 1825/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1717.7781 - root_mean_squared_error: 6416.6641 - val_loss: 1532.9314 - val_root_mean_squared_error: 5384.1733\n",
      "Epoch 1826/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1714.6821 - root_mean_squared_error: 6410.0620 - val_loss: 1524.1919 - val_root_mean_squared_error: 5273.0908\n",
      "Epoch 1827/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1701.3293 - root_mean_squared_error: 6379.9229 - val_loss: 1509.1882 - val_root_mean_squared_error: 5334.3618\n",
      "Epoch 1828/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1711.1289 - root_mean_squared_error: 6393.6235 - val_loss: 1508.9187 - val_root_mean_squared_error: 5290.0386\n",
      "Epoch 1829/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1694.8392 - root_mean_squared_error: 6363.6260 - val_loss: 1525.2706 - val_root_mean_squared_error: 5346.0620\n",
      "Epoch 1830/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1748.1821 - root_mean_squared_error: 6465.1362 - val_loss: 1512.3119 - val_root_mean_squared_error: 5381.5215\n",
      "Epoch 1831/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1699.8309 - root_mean_squared_error: 6363.3550 - val_loss: 1510.6744 - val_root_mean_squared_error: 4945.0571\n",
      "Epoch 1832/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1722.1392 - root_mean_squared_error: 6360.7124 - val_loss: 1478.0587 - val_root_mean_squared_error: 5154.5420\n",
      "Epoch 1833/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1748.8629 - root_mean_squared_error: 6494.8975 - val_loss: 1515.9592 - val_root_mean_squared_error: 5238.1963\n",
      "Epoch 1834/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1691.2781 - root_mean_squared_error: 6340.2866 - val_loss: 1500.7803 - val_root_mean_squared_error: 5103.1802\n",
      "Epoch 1835/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1710.9072 - root_mean_squared_error: 6326.3843 - val_loss: 1529.4716 - val_root_mean_squared_error: 4730.9531\n",
      "Epoch 1836/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1717.9089 - root_mean_squared_error: 6265.8838 - val_loss: 1498.0614 - val_root_mean_squared_error: 5158.5669\n",
      "Epoch 1837/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1730.1169 - root_mean_squared_error: 6350.2026 - val_loss: 1575.0956 - val_root_mean_squared_error: 5385.2231\n",
      "Epoch 1838/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1752.2072 - root_mean_squared_error: 6449.8013 - val_loss: 1506.2228 - val_root_mean_squared_error: 5293.1289\n",
      "Epoch 1839/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.8168 - root_mean_squared_error: 6406.4902 - val_loss: 1489.2744 - val_root_mean_squared_error: 4781.4297\n",
      "Epoch 1840/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1702.6489 - root_mean_squared_error: 6302.5293 - val_loss: 1492.3768 - val_root_mean_squared_error: 5025.5703\n",
      "Epoch 1841/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1746.8092 - root_mean_squared_error: 6494.3105 - val_loss: 1515.0609 - val_root_mean_squared_error: 5538.5381\n",
      "Epoch 1842/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1723.6100 - root_mean_squared_error: 6437.4575 - val_loss: 1511.2424 - val_root_mean_squared_error: 5227.6128\n",
      "Epoch 1843/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1759.6128 - root_mean_squared_error: 6364.6895 - val_loss: 1527.6501 - val_root_mean_squared_error: 4946.5708\n",
      "Epoch 1844/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1696.6481 - root_mean_squared_error: 6272.8818 - val_loss: 1496.3717 - val_root_mean_squared_error: 5013.1021\n",
      "Epoch 1845/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1725.3047 - root_mean_squared_error: 6389.7578 - val_loss: 1509.6082 - val_root_mean_squared_error: 5056.8931\n",
      "Epoch 1846/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1728.0370 - root_mean_squared_error: 6352.3115 - val_loss: 1560.3457 - val_root_mean_squared_error: 5326.4170\n",
      "Epoch 1847/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.4287 - root_mean_squared_error: 6336.0776 - val_loss: 1533.6931 - val_root_mean_squared_error: 4932.6821\n",
      "Epoch 1848/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1744.5391 - root_mean_squared_error: 6314.7866 - val_loss: 1476.2498 - val_root_mean_squared_error: 4977.2104\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1849/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1706.3146 - root_mean_squared_error: 6339.9453 - val_loss: 1487.3650 - val_root_mean_squared_error: 5160.7070\n",
      "Epoch 1850/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1709.8193 - root_mean_squared_error: 6348.9912 - val_loss: 1502.0184 - val_root_mean_squared_error: 5043.9922\n",
      "Epoch 1851/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1752.2332 - root_mean_squared_error: 6432.0513 - val_loss: 1509.8461 - val_root_mean_squared_error: 4861.4551\n",
      "Epoch 1852/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1732.1687 - root_mean_squared_error: 6391.7339 - val_loss: 1483.6176 - val_root_mean_squared_error: 5098.2666\n",
      "Epoch 1853/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1747.3494 - root_mean_squared_error: 6436.4971 - val_loss: 1496.6587 - val_root_mean_squared_error: 4810.8105\n",
      "Epoch 1854/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1769.6285 - root_mean_squared_error: 6385.1396 - val_loss: 1479.9110 - val_root_mean_squared_error: 4858.0972\n",
      "Epoch 1855/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1741.4661 - root_mean_squared_error: 6334.3115 - val_loss: 1547.3268 - val_root_mean_squared_error: 5042.5732\n",
      "Epoch 1856/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1750.2488 - root_mean_squared_error: 6344.7051 - val_loss: 1502.0941 - val_root_mean_squared_error: 4866.2510\n",
      "Epoch 1857/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1705.9437 - root_mean_squared_error: 6307.1021 - val_loss: 1480.6808 - val_root_mean_squared_error: 4805.0708\n",
      "Epoch 1858/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1707.6893 - root_mean_squared_error: 6309.2358 - val_loss: 1480.5728 - val_root_mean_squared_error: 5132.1519\n",
      "Epoch 1859/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1707.3503 - root_mean_squared_error: 6324.9648 - val_loss: 1533.1694 - val_root_mean_squared_error: 5093.6685\n",
      "Epoch 1860/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1688.8685 - root_mean_squared_error: 6258.3711 - val_loss: 1462.1969 - val_root_mean_squared_error: 4807.6196\n",
      "Epoch 1861/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1705.5105 - root_mean_squared_error: 6328.1128 - val_loss: 1475.8402 - val_root_mean_squared_error: 5070.8452\n",
      "Epoch 1862/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1745.8523 - root_mean_squared_error: 6319.4727 - val_loss: 1498.0642 - val_root_mean_squared_error: 4796.5312\n",
      "Epoch 1863/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1711.0032 - root_mean_squared_error: 6269.7134 - val_loss: 1488.8970 - val_root_mean_squared_error: 4748.1387\n",
      "Epoch 1864/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1696.5936 - root_mean_squared_error: 6265.8101 - val_loss: 1490.6846 - val_root_mean_squared_error: 4954.7446\n",
      "Epoch 1865/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1710.9738 - root_mean_squared_error: 6338.6660 - val_loss: 1458.3824 - val_root_mean_squared_error: 5007.2773\n",
      "Epoch 1866/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1699.0464 - root_mean_squared_error: 6321.0073 - val_loss: 1484.2141 - val_root_mean_squared_error: 4559.1860\n",
      "Epoch 1867/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1735.1307 - root_mean_squared_error: 6182.9800 - val_loss: 1453.3728 - val_root_mean_squared_error: 4903.7983\n",
      "Epoch 1868/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1747.5441 - root_mean_squared_error: 6388.6416 - val_loss: 1511.8030 - val_root_mean_squared_error: 5259.4604\n",
      "Epoch 1869/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1753.3383 - root_mean_squared_error: 6340.2891 - val_loss: 1537.7540 - val_root_mean_squared_error: 5087.9062\n",
      "Epoch 1870/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1782.5323 - root_mean_squared_error: 6464.7764 - val_loss: 1457.7109 - val_root_mean_squared_error: 4463.9551\n",
      "Epoch 1871/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1735.8896 - root_mean_squared_error: 6335.1968 - val_loss: 1504.7988 - val_root_mean_squared_error: 4462.6655\n",
      "Epoch 1872/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1804.3345 - root_mean_squared_error: 6356.7930 - val_loss: 1483.1914 - val_root_mean_squared_error: 4822.5864\n",
      "Epoch 1873/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1727.5127 - root_mean_squared_error: 6172.0645 - val_loss: 1522.4575 - val_root_mean_squared_error: 4692.5742\n",
      "Epoch 1874/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1720.3977 - root_mean_squared_error: 6321.6812 - val_loss: 1471.6455 - val_root_mean_squared_error: 5209.0962\n",
      "Epoch 1875/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1725.9858 - root_mean_squared_error: 6303.5020 - val_loss: 1485.4850 - val_root_mean_squared_error: 4807.4922\n",
      "Epoch 1876/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1689.5885 - root_mean_squared_error: 6270.6104 - val_loss: 1450.7593 - val_root_mean_squared_error: 4498.9482\n",
      "Epoch 1877/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1730.5035 - root_mean_squared_error: 6295.1851 - val_loss: 1449.5935 - val_root_mean_squared_error: 4736.1777\n",
      "Epoch 1878/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1689.3444 - root_mean_squared_error: 6329.6792 - val_loss: 1437.0148 - val_root_mean_squared_error: 4461.2476\n",
      "Epoch 1879/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1695.8746 - root_mean_squared_error: 6263.5742 - val_loss: 1437.2808 - val_root_mean_squared_error: 4664.9604\n",
      "Epoch 1880/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1694.0312 - root_mean_squared_error: 6244.6895 - val_loss: 1458.3831 - val_root_mean_squared_error: 4663.3818\n",
      "Epoch 1881/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1721.4939 - root_mean_squared_error: 6367.1270 - val_loss: 1434.9785 - val_root_mean_squared_error: 4216.7280\n",
      "Epoch 1882/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1730.8168 - root_mean_squared_error: 6147.5303 - val_loss: 1410.8573 - val_root_mean_squared_error: 4344.4902\n",
      "Epoch 1883/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1704.5016 - root_mean_squared_error: 6264.8359 - val_loss: 1468.3046 - val_root_mean_squared_error: 4829.8760\n",
      "Epoch 1884/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1701.1787 - root_mean_squared_error: 6296.9458 - val_loss: 1434.0750 - val_root_mean_squared_error: 4719.3086\n",
      "Epoch 1885/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1733.7966 - root_mean_squared_error: 6267.1035 - val_loss: 1463.2853 - val_root_mean_squared_error: 4471.0244\n",
      "Epoch 1886/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1686.5927 - root_mean_squared_error: 6252.7197 - val_loss: 1437.8435 - val_root_mean_squared_error: 4666.3779\n",
      "Epoch 1887/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1681.4269 - root_mean_squared_error: 6257.0684 - val_loss: 1437.6067 - val_root_mean_squared_error: 4599.4399\n",
      "Epoch 1888/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1697.7225 - root_mean_squared_error: 6241.2090 - val_loss: 1438.4941 - val_root_mean_squared_error: 4407.1328\n",
      "Epoch 1889/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1704.0448 - root_mean_squared_error: 6293.8931 - val_loss: 1413.2560 - val_root_mean_squared_error: 4566.7207\n",
      "Epoch 1890/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1696.1646 - root_mean_squared_error: 6255.4121 - val_loss: 1421.3563 - val_root_mean_squared_error: 4392.5532\n",
      "Epoch 1891/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1683.0905 - root_mean_squared_error: 6293.7178 - val_loss: 1417.5896 - val_root_mean_squared_error: 4636.4189\n",
      "Epoch 1892/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1677.1550 - root_mean_squared_error: 6299.1855 - val_loss: 1423.4586 - val_root_mean_squared_error: 4300.8984\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1893/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1677.0452 - root_mean_squared_error: 6223.6133 - val_loss: 1437.2203 - val_root_mean_squared_error: 4627.0664\n",
      "Epoch 1894/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1758.0225 - root_mean_squared_error: 6239.6035 - val_loss: 1421.7018 - val_root_mean_squared_error: 4248.0073\n",
      "Epoch 1895/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1738.8959 - root_mean_squared_error: 6235.9614 - val_loss: 1414.3605 - val_root_mean_squared_error: 4360.9019\n",
      "Epoch 1896/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1697.9658 - root_mean_squared_error: 6208.7017 - val_loss: 1427.7164 - val_root_mean_squared_error: 4429.2153\n",
      "Epoch 1897/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1695.3558 - root_mean_squared_error: 6252.1416 - val_loss: 1388.1409 - val_root_mean_squared_error: 4124.9844\n",
      "Epoch 1898/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1681.4725 - root_mean_squared_error: 6213.7319 - val_loss: 1413.9170 - val_root_mean_squared_error: 4421.0688\n",
      "Epoch 1899/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1701.0582 - root_mean_squared_error: 6279.4473 - val_loss: 1401.4911 - val_root_mean_squared_error: 4339.5410\n",
      "Epoch 1900/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1677.9218 - root_mean_squared_error: 6178.6816 - val_loss: 1406.9928 - val_root_mean_squared_error: 4149.7974\n",
      "Epoch 1901/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1709.1093 - root_mean_squared_error: 6169.8730 - val_loss: 1400.0721 - val_root_mean_squared_error: 4020.7163\n",
      "Epoch 1902/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1706.5565 - root_mean_squared_error: 6144.3931 - val_loss: 1399.8054 - val_root_mean_squared_error: 4009.2502\n",
      "Epoch 1903/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1716.6372 - root_mean_squared_error: 6252.6792 - val_loss: 1406.1970 - val_root_mean_squared_error: 4077.6177\n",
      "Epoch 1904/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1674.5652 - root_mean_squared_error: 6229.5532 - val_loss: 1382.0654 - val_root_mean_squared_error: 4218.2021\n",
      "Epoch 1905/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1689.0988 - root_mean_squared_error: 6208.4805 - val_loss: 1381.3464 - val_root_mean_squared_error: 4088.5364\n",
      "Epoch 1906/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1705.7634 - root_mean_squared_error: 6111.1411 - val_loss: 1393.5018 - val_root_mean_squared_error: 4263.2280\n",
      "Epoch 1907/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1700.4321 - root_mean_squared_error: 6182.9106 - val_loss: 1418.1255 - val_root_mean_squared_error: 4277.4551\n",
      "Epoch 1908/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1695.8440 - root_mean_squared_error: 6203.9131 - val_loss: 1375.8749 - val_root_mean_squared_error: 4164.7783\n",
      "Epoch 1909/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1700.5426 - root_mean_squared_error: 6163.5093 - val_loss: 1375.1752 - val_root_mean_squared_error: 4157.5674\n",
      "Epoch 1910/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1696.4905 - root_mean_squared_error: 6185.8145 - val_loss: 1375.1780 - val_root_mean_squared_error: 4060.0408\n",
      "Epoch 1911/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1681.5288 - root_mean_squared_error: 6226.7065 - val_loss: 1391.8737 - val_root_mean_squared_error: 4224.3760\n",
      "Epoch 1912/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1671.8989 - root_mean_squared_error: 6186.2876 - val_loss: 1366.0884 - val_root_mean_squared_error: 4052.9304\n",
      "Epoch 1913/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1664.1647 - root_mean_squared_error: 6164.8472 - val_loss: 1379.8342 - val_root_mean_squared_error: 3838.2241\n",
      "Epoch 1914/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1722.4852 - root_mean_squared_error: 6137.2622 - val_loss: 1350.3990 - val_root_mean_squared_error: 4095.0571\n",
      "Epoch 1915/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1736.6794 - root_mean_squared_error: 6146.1714 - val_loss: 1455.6200 - val_root_mean_squared_error: 4077.0901\n",
      "Epoch 1916/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1721.6813 - root_mean_squared_error: 6105.2837 - val_loss: 1451.4900 - val_root_mean_squared_error: 4209.6128\n",
      "Epoch 1917/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1756.1940 - root_mean_squared_error: 6078.5737 - val_loss: 1380.5417 - val_root_mean_squared_error: 3802.7903\n",
      "Epoch 1918/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1717.5472 - root_mean_squared_error: 6132.8833 - val_loss: 1365.6833 - val_root_mean_squared_error: 4010.8350\n",
      "Epoch 1919/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1691.0784 - root_mean_squared_error: 6216.3325 - val_loss: 1378.8315 - val_root_mean_squared_error: 3986.0303\n",
      "Epoch 1920/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1667.7694 - root_mean_squared_error: 6164.2808 - val_loss: 1370.0687 - val_root_mean_squared_error: 4094.8655\n",
      "Epoch 1921/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1669.6279 - root_mean_squared_error: 6175.9355 - val_loss: 1382.3666 - val_root_mean_squared_error: 3965.4126\n",
      "Epoch 1922/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1688.9651 - root_mean_squared_error: 6140.3481 - val_loss: 1351.9592 - val_root_mean_squared_error: 3698.7329\n",
      "Epoch 1923/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1716.1128 - root_mean_squared_error: 6196.0884 - val_loss: 1359.3359 - val_root_mean_squared_error: 4235.3159\n",
      "Epoch 1924/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1710.4824 - root_mean_squared_error: 6253.0483 - val_loss: 1414.7882 - val_root_mean_squared_error: 3939.5134\n",
      "Epoch 1925/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1703.9504 - root_mean_squared_error: 6202.2969 - val_loss: 1371.2544 - val_root_mean_squared_error: 4013.2454\n",
      "Epoch 1926/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1691.7644 - root_mean_squared_error: 6125.3237 - val_loss: 1400.6157 - val_root_mean_squared_error: 3871.6028\n",
      "Epoch 1927/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1691.3181 - root_mean_squared_error: 6198.5039 - val_loss: 1357.2765 - val_root_mean_squared_error: 3667.8916\n",
      "Epoch 1928/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1732.4734 - root_mean_squared_error: 6124.6182 - val_loss: 1395.0297 - val_root_mean_squared_error: 3851.8196\n",
      "Epoch 1929/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1728.6097 - root_mean_squared_error: 6193.5459 - val_loss: 1387.2081 - val_root_mean_squared_error: 4195.0381\n",
      "Epoch 1930/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1702.5541 - root_mean_squared_error: 6197.8540 - val_loss: 1401.5972 - val_root_mean_squared_error: 3990.0801\n",
      "Epoch 1931/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1709.6471 - root_mean_squared_error: 6085.7285 - val_loss: 1357.1829 - val_root_mean_squared_error: 3699.5286\n",
      "Epoch 1932/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1709.5782 - root_mean_squared_error: 6133.2012 - val_loss: 1339.0217 - val_root_mean_squared_error: 3873.2935\n",
      "Epoch 1933/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1669.8385 - root_mean_squared_error: 6171.7769 - val_loss: 1340.8817 - val_root_mean_squared_error: 3920.2234\n",
      "Epoch 1934/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1660.1465 - root_mean_squared_error: 6140.6680 - val_loss: 1358.8110 - val_root_mean_squared_error: 3814.7002\n",
      "Epoch 1935/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1665.2838 - root_mean_squared_error: 6163.7393 - val_loss: 1348.5638 - val_root_mean_squared_error: 3856.0735\n",
      "Epoch 1936/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1660.4603 - root_mean_squared_error: 6080.1284 - val_loss: 1319.4678 - val_root_mean_squared_error: 3551.7842\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1937/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1680.7660 - root_mean_squared_error: 6121.7881 - val_loss: 1316.4088 - val_root_mean_squared_error: 3626.6758\n",
      "Epoch 1938/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1666.2465 - root_mean_squared_error: 6107.0034 - val_loss: 1338.0553 - val_root_mean_squared_error: 3695.6460\n",
      "Epoch 1939/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1681.5352 - root_mean_squared_error: 6145.1177 - val_loss: 1315.0957 - val_root_mean_squared_error: 3551.0374\n",
      "Epoch 1940/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1681.1351 - root_mean_squared_error: 6177.1587 - val_loss: 1312.6045 - val_root_mean_squared_error: 3786.1077\n",
      "Epoch 1941/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1675.1615 - root_mean_squared_error: 6133.5400 - val_loss: 1320.5872 - val_root_mean_squared_error: 3364.5928\n",
      "Epoch 1942/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1695.3511 - root_mean_squared_error: 6131.1353 - val_loss: 1288.8947 - val_root_mean_squared_error: 3575.0881\n",
      "Epoch 1943/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1668.6272 - root_mean_squared_error: 6109.8823 - val_loss: 1333.7164 - val_root_mean_squared_error: 3904.9399\n",
      "Epoch 1944/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1670.3379 - root_mean_squared_error: 6132.6416 - val_loss: 1353.8463 - val_root_mean_squared_error: 3718.3040\n",
      "Epoch 1945/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1667.9806 - root_mean_squared_error: 6073.6738 - val_loss: 1327.3173 - val_root_mean_squared_error: 3496.0562\n",
      "Epoch 1946/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1670.8696 - root_mean_squared_error: 6122.1646 - val_loss: 1316.1959 - val_root_mean_squared_error: 3388.5181\n",
      "Epoch 1947/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1689.8268 - root_mean_squared_error: 6160.4868 - val_loss: 1319.8583 - val_root_mean_squared_error: 3393.6362\n",
      "Epoch 1948/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1707.1943 - root_mean_squared_error: 6138.7778 - val_loss: 1311.6453 - val_root_mean_squared_error: 3364.1658\n",
      "Epoch 1949/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1701.9194 - root_mean_squared_error: 6152.8979 - val_loss: 1314.2302 - val_root_mean_squared_error: 3666.7859\n",
      "Epoch 1950/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1705.9291 - root_mean_squared_error: 6178.2036 - val_loss: 1319.8638 - val_root_mean_squared_error: 3495.9788\n",
      "Epoch 1951/2000\n",
      "10/10 [==============================] - 0s 7ms/step - loss: 1709.2587 - root_mean_squared_error: 6126.1206 - val_loss: 1348.4963 - val_root_mean_squared_error: 3606.6196\n",
      "Epoch 1952/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1697.8239 - root_mean_squared_error: 6106.1665 - val_loss: 1321.8855 - val_root_mean_squared_error: 3608.6323\n",
      "Epoch 1953/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1685.0483 - root_mean_squared_error: 6056.8667 - val_loss: 1325.3759 - val_root_mean_squared_error: 3486.0618\n",
      "Epoch 1954/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1677.8667 - root_mean_squared_error: 6074.5332 - val_loss: 1304.6801 - val_root_mean_squared_error: 3616.2517\n",
      "Epoch 1955/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1668.9143 - root_mean_squared_error: 6148.2783 - val_loss: 1303.8915 - val_root_mean_squared_error: 3580.7397\n",
      "Epoch 1956/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1661.1362 - root_mean_squared_error: 6078.7485 - val_loss: 1280.0471 - val_root_mean_squared_error: 3346.3748\n",
      "Epoch 1957/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1682.2523 - root_mean_squared_error: 6120.9282 - val_loss: 1285.2461 - val_root_mean_squared_error: 3362.8635\n",
      "Epoch 1958/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1686.6317 - root_mean_squared_error: 6019.3076 - val_loss: 1242.8499 - val_root_mean_squared_error: 3233.8704\n",
      "Epoch 1959/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1662.4293 - root_mean_squared_error: 6045.2275 - val_loss: 1278.8370 - val_root_mean_squared_error: 3358.4214\n",
      "Epoch 1960/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1658.0249 - root_mean_squared_error: 6066.9424 - val_loss: 1255.1082 - val_root_mean_squared_error: 3429.6941\n",
      "Epoch 1961/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1667.1635 - root_mean_squared_error: 6045.5693 - val_loss: 1291.6986 - val_root_mean_squared_error: 3482.9800\n",
      "Epoch 1962/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1650.1639 - root_mean_squared_error: 6047.6318 - val_loss: 1287.8164 - val_root_mean_squared_error: 3385.9424\n",
      "Epoch 1963/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1664.9718 - root_mean_squared_error: 6119.4395 - val_loss: 1296.1267 - val_root_mean_squared_error: 3381.2024\n",
      "Epoch 1964/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1735.6752 - root_mean_squared_error: 6057.0957 - val_loss: 1293.5836 - val_root_mean_squared_error: 3302.4976\n",
      "Epoch 1965/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1703.3677 - root_mean_squared_error: 5976.8433 - val_loss: 1342.4033 - val_root_mean_squared_error: 3393.4583\n",
      "Epoch 1966/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1715.1768 - root_mean_squared_error: 6104.6313 - val_loss: 1274.2725 - val_root_mean_squared_error: 3414.5298\n",
      "Epoch 1967/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1756.0496 - root_mean_squared_error: 6252.8555 - val_loss: 1316.5081 - val_root_mean_squared_error: 3282.1335\n",
      "Epoch 1968/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1686.7672 - root_mean_squared_error: 5997.0898 - val_loss: 1256.9034 - val_root_mean_squared_error: 3327.8784\n",
      "Epoch 1969/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1664.6768 - root_mean_squared_error: 6055.4087 - val_loss: 1270.6262 - val_root_mean_squared_error: 3236.4705\n",
      "Epoch 1970/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1643.1146 - root_mean_squared_error: 6064.7651 - val_loss: 1251.3821 - val_root_mean_squared_error: 3237.3926\n",
      "Epoch 1971/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1658.7812 - root_mean_squared_error: 6013.1963 - val_loss: 1287.7054 - val_root_mean_squared_error: 3407.9917\n",
      "Epoch 1972/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1678.0166 - root_mean_squared_error: 6039.3394 - val_loss: 1283.0521 - val_root_mean_squared_error: 3301.6865\n",
      "Epoch 1973/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1693.0928 - root_mean_squared_error: 6174.8574 - val_loss: 1225.7782 - val_root_mean_squared_error: 2943.5798\n",
      "Epoch 1974/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1701.3687 - root_mean_squared_error: 6132.5542 - val_loss: 1216.0717 - val_root_mean_squared_error: 3036.2083\n",
      "Epoch 1975/2000\n",
      "10/10 [==============================] - 0s 6ms/step - loss: 1705.4636 - root_mean_squared_error: 6256.9580 - val_loss: 1297.2441 - val_root_mean_squared_error: 3336.6565\n",
      "Epoch 1976/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1698.0038 - root_mean_squared_error: 6132.2729 - val_loss: 1286.2537 - val_root_mean_squared_error: 3244.7407\n",
      "Epoch 1977/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1706.4821 - root_mean_squared_error: 6081.6099 - val_loss: 1275.1201 - val_root_mean_squared_error: 3108.9866\n",
      "Epoch 1978/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1713.0922 - root_mean_squared_error: 6144.2017 - val_loss: 1217.1375 - val_root_mean_squared_error: 3370.2969\n",
      "Epoch 1979/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1676.5701 - root_mean_squared_error: 6072.7036 - val_loss: 1278.7249 - val_root_mean_squared_error: 3306.9568\n",
      "Epoch 1980/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1676.6890 - root_mean_squared_error: 6030.5933 - val_loss: 1290.0978 - val_root_mean_squared_error: 3336.4717\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1981/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1697.2180 - root_mean_squared_error: 6007.4062 - val_loss: 1260.6688 - val_root_mean_squared_error: 3265.2659\n",
      "Epoch 1982/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1679.4773 - root_mean_squared_error: 6059.9658 - val_loss: 1260.0469 - val_root_mean_squared_error: 2994.1482\n",
      "Epoch 1983/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1691.6650 - root_mean_squared_error: 6007.1685 - val_loss: 1212.7015 - val_root_mean_squared_error: 3114.8928\n",
      "Epoch 1984/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1677.7657 - root_mean_squared_error: 6137.0610 - val_loss: 1275.6774 - val_root_mean_squared_error: 3222.8506\n",
      "Epoch 1985/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1789.2490 - root_mean_squared_error: 6150.4316 - val_loss: 1276.6373 - val_root_mean_squared_error: 3022.8804\n",
      "Epoch 1986/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1693.0933 - root_mean_squared_error: 5995.1528 - val_loss: 1240.1979 - val_root_mean_squared_error: 3209.6626\n",
      "Epoch 1987/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1665.9894 - root_mean_squared_error: 6137.2959 - val_loss: 1258.6831 - val_root_mean_squared_error: 3146.9919\n",
      "Epoch 1988/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1651.0529 - root_mean_squared_error: 6075.4819 - val_loss: 1235.1448 - val_root_mean_squared_error: 3038.8337\n",
      "Epoch 1989/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1706.4089 - root_mean_squared_error: 6050.8706 - val_loss: 1249.0563 - val_root_mean_squared_error: 3027.2712\n",
      "Epoch 1990/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1725.5112 - root_mean_squared_error: 6107.7485 - val_loss: 1229.6062 - val_root_mean_squared_error: 3281.1116\n",
      "Epoch 1991/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1734.1289 - root_mean_squared_error: 6109.2246 - val_loss: 1236.3160 - val_root_mean_squared_error: 2993.2676\n",
      "Epoch 1992/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1710.0922 - root_mean_squared_error: 6047.1787 - val_loss: 1310.9941 - val_root_mean_squared_error: 3162.1653\n",
      "Epoch 1993/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1793.9645 - root_mean_squared_error: 6131.9604 - val_loss: 1253.3502 - val_root_mean_squared_error: 3103.6506\n",
      "Epoch 1994/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1664.9315 - root_mean_squared_error: 6050.8057 - val_loss: 1212.6125 - val_root_mean_squared_error: 2967.8850\n",
      "Epoch 1995/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1649.1132 - root_mean_squared_error: 6027.7183 - val_loss: 1248.6259 - val_root_mean_squared_error: 3137.6292\n",
      "Epoch 1996/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1660.8564 - root_mean_squared_error: 6001.3477 - val_loss: 1209.7513 - val_root_mean_squared_error: 3092.4890\n",
      "Epoch 1997/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1645.4456 - root_mean_squared_error: 6013.3555 - val_loss: 1202.3945 - val_root_mean_squared_error: 2897.2505\n",
      "Epoch 1998/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1655.9730 - root_mean_squared_error: 6038.8877 - val_loss: 1195.8220 - val_root_mean_squared_error: 3075.6375\n",
      "Epoch 1999/2000\n",
      "10/10 [==============================] - 0s 4ms/step - loss: 1707.5787 - root_mean_squared_error: 6095.6411 - val_loss: 1256.9255 - val_root_mean_squared_error: 3049.4297\n",
      "Epoch 2000/2000\n",
      "10/10 [==============================] - 0s 5ms/step - loss: 1714.3433 - root_mean_squared_error: 6035.0474 - val_loss: 1225.9108 - val_root_mean_squared_error: 2946.5725\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x14066db1688>"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NN_model.fit(X_train, y_train, epochs=2000, batch_size=64, validation_split = 0.1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "_jNOZGuHZEc5"
   },
   "outputs": [],
   "source": [
    "losses = pd.DataFrame(NN_model.history.history)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "colab_type": "code",
    "id": "QFxfE-9xZEc9",
    "outputId": "bc603360-937d-4078-d5d1-cc582f6ff58e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1406a7eea88>"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "losses.plot()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluation on Test Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "nlzGzbiIrK68"
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error,mean_absolute_error,explained_variance_score,r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "zvyiwhoLrmK8"
   },
   "outputs": [],
   "source": [
    "predictions = NN_model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "u_I9ZVnkru59",
    "outputId": "a54edb99-e19a-4807-bedb-d1e8e1f97186"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5428413489663901"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_test,predictions)  #Test data R2 Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "dRo2up84Ig2C"
   },
   "outputs": [],
   "source": [
    "predictions_1=NN_model.predict(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "H290Ni21Ip2n",
    "outputId": "b289489f-e2e2-4297-a114-4217ee6da19e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8222595976421981"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_train,predictions_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "uAEJ6SNor21Z",
    "outputId": "b73a8baa-7c50-4978-9f45-75eb9f259a4f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5589516685626987"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "explained_variance_score(y_test,predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prediction on Competition Testing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Finding Output:\n",
    "def predict_values(test1):\n",
    "    missing_values_plot(test1)\n",
    "    \n",
    "    feature=[\"Population [2011]\",\"Toilets Avl\",\"# of hospitals\",\"Foreign Visitors\"]\n",
    "    test_df=missing_values_handling(test1,feature)\n",
    "    \n",
    "    correlation_circle(test_df,feature)\n",
    "    test_array=test_df.to_numpy()\n",
    "    test_array=scaler.transform(test_array)  #Scaling the test data\n",
    "    \n",
    "    predictions_test=NN_model.predict(test_array)\n",
    "    \n",
    "    return predictions_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Making the submission file\n",
    "def submission(city):\n",
    "    predictions_test=predict_values(test1)\n",
    "    \n",
    "    city_1=pd.DataFrame(city,columns=[\"City\"])\n",
    "    test_predictions_df=pd.DataFrame(predictions_test,columns=[\"Covid Cases\"])\n",
    "    final_test=pd.concat([city_1,test_predictions_df],axis=1)\n",
    "   \n",
    "    return final_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 1 Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   Missing  All\n",
      "Population [2011]        0  501\n",
      "Toilets Avl              0  501\n",
      "# of hospitals           0  501\n",
      "Foreign Visitors         0  501\n",
      "CSV FILE CREATED!!\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Part 1 predictions\n",
    "test=pd.read_excel('Test_dataset.xlsx')\n",
    "test1=test.drop(columns=[\"City\",\"State\",\"Type\",\"Popuation [2001]\",\"Sex Ratio\",\"Median Age\",\"SWM\",\"Avg Temp\",\"Water Purity\",\"H Index\",\"Female Population\"])\n",
    "final_test_part1=submission(test[\"City\"])\n",
    "final_test_part1.to_csv(\"Submission_Part_1.csv\")\n",
    "print(\"CSV FILE CREATED!!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task 2 Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   Missing  All\n",
      "Population [2011]        0  501\n",
      "Toilets Avl              0  501\n",
      "# of hospitals           0  501\n",
      "Foreign Visitors         0  501\n",
      "CSV FILE CREATED!!\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Part 2 using data from Time Series Model\n",
    "test=pd.read_excel('T2Test_dataset.xlsx')\n",
    "test1=test.drop(columns=[\"Index\",\"City\",\"State\",\"Type\",\"Popuation [2001]\",\"Sex Ratio\",\"Median Age\",\"SWM\",\"Avg Temp\",\"Water Purity\",\"H Index\",\"Female Population\"])\n",
    "final_test_part2=submission(test[\"City\"])\n",
    "final_test_part2.to_csv(\"Submission_Part_2.csv\")\n",
    "print(\"CSV FILE CREATED!!\")"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "name": "Flipr notebook updated.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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}