{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dcfc86c4-016e-491c-bcb9-a83e422fe662",
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing the libraries\n",
    "\n",
    "#Data Processing Libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "#Data Vizualization Libraries\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Pretty display for notebooks\n",
    "%matplotlib inline\n",
    "\n",
    "# Machine Learning Library\n",
    "from sklearn.preprocessing import LabelEncoder # Encode Categorical Variable to Numerical Variable\n",
    "from sklearn.impute import SimpleImputer # Imputer Class to replace missing values\n",
    "from sklearn.metrics import confusion_matrix # Library for model evaluation\n",
    "from sklearn.metrics import accuracy_score # Library for model evaluation\n",
    "from sklearn.model_selection import train_test_split # Library to split datset into test and train\n",
    "\n",
    "from sklearn.linear_model  import LogisticRegression # Logistic Regression Classifier\n",
    "from sklearn.linear_model import SGDClassifier # Stochastic Gradient Descent Classifier\n",
    "from sklearn.tree import DecisionTreeClassifier # Decision Tree Classifier\n",
    "from sklearn.ensemble  import RandomForestClassifier # Random Forest Classifier\n",
    "from sklearn.neighbors import KNeighborsClassifier # K Nearest neighbors Classifier\n",
    "from sklearn.naive_bayes import GaussianNB #Naive Bayes Classifier\n",
    "from sklearn.svm import SVC #Support vector Machine Classifier\n",
    "from sklearn.ensemble import AdaBoostClassifier # Ada Boost Classifier\n",
    "from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, classification_report, confusion_matrix\n",
    "from sklearn.model_selection import cross_val_score"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "facf83da-c514-4c8a-ba97-889b463e1fc3",
   "metadata": {},
   "source": [
    "### Load dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "876bf9a7-98ae-4608-9764-1e7af706c971",
   "metadata": {},
   "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>SeniorCitizen</th>\n",
       "      <th>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7032.000000</td>\n",
       "      <td>7032.000000</td>\n",
       "      <td>7032.000000</td>\n",
       "      <td>7032.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.162400</td>\n",
       "      <td>32.421786</td>\n",
       "      <td>64.798208</td>\n",
       "      <td>2283.300441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.368844</td>\n",
       "      <td>24.545260</td>\n",
       "      <td>30.085974</td>\n",
       "      <td>2266.771362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>18.250000</td>\n",
       "      <td>18.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>35.587500</td>\n",
       "      <td>401.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>70.350000</td>\n",
       "      <td>1397.475000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>89.862500</td>\n",
       "      <td>3794.737500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>118.750000</td>\n",
       "      <td>8684.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       SeniorCitizen       tenure  MonthlyCharges  TotalCharges\n",
       "count    7032.000000  7032.000000     7032.000000   7032.000000\n",
       "mean        0.162400    32.421786       64.798208   2283.300441\n",
       "std         0.368844    24.545260       30.085974   2266.771362\n",
       "min         0.000000     1.000000       18.250000     18.800000\n",
       "25%         0.000000     9.000000       35.587500    401.450000\n",
       "50%         0.000000    29.000000       70.350000   1397.475000\n",
       "75%         0.000000    55.000000       89.862500   3794.737500\n",
       "max         1.000000    72.000000      118.750000   8684.800000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('telco.csv')\n",
    "df.describe()\n",
    "#df[df['TotalCharges'] == ' '].index"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab207ef8-ab57-4b6c-9234-47b84a4cc59f",
   "metadata": {},
   "source": [
    "### Exporatory Data Analysis (EDA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e2dfd307-e88e-4413-b58d-820e48e57877",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Churn', ylabel='count'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Q888/L6/XK0kdruLU1tY6V428Xq9aW1sVDocvOHPy5MkOr1tXV9fh6hMAADBTp4Lo7bffVmtra4ftf/rTn/TrX//6ihZk27ZaWlo0bNgweb1e7d6929nX2tqq0tJSjR8/XpI0ZswY9evXL2qmpqZGhw8fdmYCgYAikYjKy//vpsz9+/crEok4MwAAwGyX9ZbZe++95/zv3/72t1FXb9rb2xUMBvVXf/VXl3y8xx57TDNmzJDf71djY6O2bdumt99+W8FgUC6XS/n5+SosLFRqaqpSU1NVWFioAQMGKDc3V5JkWZbmzp2rpUuXavDgwUpKStKyZcuUnp6uzMxMSdLIkSM1ffp0zZs3T+vXr5ckzZ8/X1lZWV/4CTMAAGCWywqiO++8Uy6XSy6X67xvjcXHx+uFF1645OOdPHlSeXl5qqmpkWVZGj16tILBoKZMmSJJWr58uZqbm7VgwQKFw2FlZGRo165dSkhIcI6xZs0axcXFKScnR83NzZo8ebJKSkrUt29fZ2bLli1avHix82m07OxsFRcXX86pAwCAa9hlfQ/RH//4R9m2rVtuuUXl5eVKTk529vXv318pKSlRIXItudTvMbhSfA8R0BHfQwSgsy719/dlXSEaOnSoJOnMmTNXtjoAAIAepNMfu//d736nt99+W7W1tR0C6cknn7zihQEAAHSXTgXRhg0b9E//9E8aMmSIvF5vh+/8IYgAAEBv0qkg+t73vqd/+7d/c/7GGAAAQG/Wqe8hCofDevDBB6/2WgAAAGKiU0H04IMPateuXVd7LQAAADHRqbfMbr31Vj3xxBMqKytTenq6+vXrF7V/8eLFV2VxAAAA3eGyvoforGHDhn3xAV0uffjhh1e0qJ6I7yECYofvIQLQWV3yPURnVVdXd3phAAAAPU2n7iECAAC4lnTqCtGcOXMuuP/ll1/u1GIAAABioVNBFA6Ho563tbXp8OHDqq+vP+8ffQUAAOjJOhVEO3bs6LDtzJkzWrBggW655ZYrXhQAAEB3umr3EPXp00f//M//rDVr1lytQwIAAHSLq3pT9e9//3v9+c9/vpqHBAAA6HKdestsyZIlUc9t21ZNTY1effVVzZo166osDAAAoLt0KojefffdqOd9+vRRcnKynnvuuYt+Ag0AAKCn6VQQvfXWW1d7HQAAADHTqSA6q66uTkePHpXL5dLw4cOVnJx8tdYFAADQbTp1U/Xp06c1Z84c3Xjjjbr77rv1ta99TT6fT3PnztVnn312tdcIAADQpToVREuWLFFpaan++7//W/X19aqvr9fPf/5zlZaWaunSpVd7jQAAAF2qU2+Zbd++Xa+88oomTZrkbLv33nsVHx+vnJwcrVu37mqtDwAAoMt16grRZ599Jo/H02F7SkoKb5kBAIBep1NBFAgE9J3vfEd/+tOfnG3Nzc166qmnFAgErtriAAAAukOn3jJbu3atZsyYoZtuukl33HGHXC6XKisr5Xa7tWvXrqu9RgAAgC7VqSBKT0/XsWPHtHnzZr3//vuybVsPP/ywZs6cqfj4+Ku9RgAAgC7VqSAqKiqSx+PRvHnzora//PLLqqur04oVK67K4gAAALpDp+4hWr9+vW677bYO22+//Xb9x3/8xxUvCgAAoDt1KohCoZBuvPHGDtuTk5NVU1NzxYsCAADoTp0KIr/fr3feeafD9nfeeUc+n++KFwUAANCdOnUP0Te+8Q3l5+erra1N99xzjyTpzTff1PLly/mmagAA0Ot0KoiWL1+uU6dOacGCBWptbZUkXXfddVqxYoVWrlx5VRcIAADQ1Vy2bdud/eGmpiZVVVUpPj5eqampcrvdV3NtPUpDQ4Msy1IkElFiYmKXvU7F2Lu67NhAbzW2ojzWSwDQS13q7+9OXSE66/rrr9dXv/rVKzkEAABAzHXqpmoAAIBrCUEEAACMRxABAADjEUQAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEQAAMB5BBAAAjEcQAQAA4xFEAADAeAQRAAAwHkEEAACMRxABAADjEUQAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEQAAMB5BBAAAjEcQAQAA48U0iIqKivTVr35VCQkJSklJ0d/93d/p6NGjUTO2baugoEA+n0/x8fGaNGmSjhw5EjXT0tKiRYsWaciQIRo4cKCys7N14sSJqJlwOKy8vDxZliXLspSXl6f6+vquPkUAANALxDSISktLtXDhQpWVlWn37t3685//rKlTp+r06dPOzKpVq7R69WoVFxfrwIED8nq9mjJlihobG52Z/Px87dixQ9u2bdOePXvU1NSkrKwstbe3OzO5ubmqrKxUMBhUMBhUZWWl8vLyuvV8AQBAz+SybduO9SLOqqurU0pKikpLS3X33XfLtm35fD7l5+drxYoVkv5yNcjj8ejZZ5/Vo48+qkgkouTkZG3atEkPPfSQJOnjjz+W3+/Xa6+9pmnTpqmqqkqjRo1SWVmZMjIyJEllZWUKBAJ6//33NWLEiA5raWlpUUtLi/O8oaFBfr9fkUhEiYmJXfbfoGLsXV12bKC3GltRHuslAOilGhoaZFnWRX9/96h7iCKRiCQpKSlJklRdXa1QKKSpU6c6M263WxMnTtTevXslSQcPHlRbW1vUjM/nU1pamjOzb98+WZblxJAkjRs3TpZlOTPnKioqct5esyxLfr//6p4sAADoMXpMENm2rSVLluiv//qvlZaWJkkKhUKSJI/HEzXr8XicfaFQSP3799egQYMuOJOSktLhNVNSUpyZc61cuVKRSMR5HD9+/MpOEAAA9FhxsV7AWd/61rf03nvvac+ePR32uVyuqOe2bXfYdq5zZ843f6HjuN1uud3uS1k6AADo5XrEFaJFixbpF7/4hd566y3ddNNNznav1ytJHa7i1NbWOleNvF6vWltbFQ6HLzhz8uTJDq9bV1fX4eoTAAAwT0yDyLZtfetb39LPfvYz/e///q+GDRsWtX/YsGHyer3avXu3s621tVWlpaUaP368JGnMmDHq169f1ExNTY0OHz7szAQCAUUiEZWX/9+Nmfv371ckEnFmAACAuWL6ltnChQu1detW/fznP1dCQoJzJciyLMXHx8vlcik/P1+FhYVKTU1VamqqCgsLNWDAAOXm5jqzc+fO1dKlSzV48GAlJSVp2bJlSk9PV2ZmpiRp5MiRmj59uubNm6f169dLkubPn6+srKzzfsIMAACYJaZBtG7dOknSpEmTorb/+Mc/1uzZsyVJy5cvV3NzsxYsWKBwOKyMjAzt2rVLCQkJzvyaNWsUFxennJwcNTc3a/LkySopKVHfvn2dmS1btmjx4sXOp9Gys7NVXFzctScIAAB6hR71PUQ92aV+j8GV4nuIgI74HiIAndUrv4cIAAAgFnrMx+4B4Fo3/YmfxHoJQI8TfPqhWC9BEleIAAAACCIAAACCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYL6ZB9Ktf/Ur33XeffD6fXC6Xdu7cGbXftm0VFBTI5/MpPj5ekyZN0pEjR6JmWlpatGjRIg0ZMkQDBw5Udna2Tpw4ETUTDoeVl5cny7JkWZby8vJUX1/fxWcHAAB6i5gG0enTp3XHHXeouLj4vPtXrVql1atXq7i4WAcOHJDX69WUKVPU2NjozOTn52vHjh3atm2b9uzZo6amJmVlZam9vd2Zyc3NVWVlpYLBoILBoCorK5WXl9fl5wcAAHqHuFi++IwZMzRjxozz7rNtW2vXrtXjjz+uBx54QJK0ceNGeTwebd26VY8++qgikYheeuklbdq0SZmZmZKkzZs3y+/364033tC0adNUVVWlYDCosrIyZWRkSJI2bNigQCCgo0ePasSIEd1zsgAAoMfqsfcQVVdXKxQKaerUqc42t9utiRMnau/evZKkgwcPqq2tLWrG5/MpLS3Nmdm3b58sy3JiSJLGjRsny7KcmfNpaWlRQ0ND1AMAAFybemwQhUIhSZLH44na7vF4nH2hUEj9+/fXoEGDLjiTkpLS4fgpKSnOzPkUFRU59xxZliW/339F5wMAAHquHhtEZ7lcrqjntm132Hauc2fON3+x46xcuVKRSMR5HD9+/DJXDgAAeoseG0Rer1eSOlzFqa2tda4aeb1etba2KhwOX3Dm5MmTHY5fV1fX4erT57ndbiUmJkY9AADAtanHBtGwYcPk9Xq1e/duZ1tra6tKS0s1fvx4SdKYMWPUr1+/qJmamhodPnzYmQkEAopEIiovL3dm9u/fr0gk4swAAACzxfRTZk1NTfrggw+c59XV1aqsrFRSUpJuvvlm5efnq7CwUKmpqUpNTVVhYaEGDBig3NxcSZJlWZo7d66WLl2qwYMHKykpScuWLVN6errzqbORI0dq+vTpmjdvntavXy9Jmj9/vrKysviEGQAAkBTjIKqoqNDXv/515/mSJUskSbNmzVJJSYmWL1+u5uZmLViwQOFwWBkZGdq1a5cSEhKcn1mzZo3i4uKUk5Oj5uZmTZ48WSUlJerbt68zs2XLFi1evNj5NFp2dvYXfvcRAAAwj8u2bTvWi+gNGhoaZFmWIpFIl95PVDH2ri47NtBbja0ov/hQLzD9iZ/EeglAjxN8+qEuPf6l/v7usfcQAQAAdBeCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8gggAABiPIAIAAMYjiAAAgPEIIgAAYDyCCAAAGI8gAgAAxiOIAACA8QgiAABgPIIIAAAYjyACAADGI4gAAIDxCCIAAGA8o4LoxRdf1LBhw3TddddpzJgx+vWvfx3rJQEAgB7AmCD6yU9+ovz8fD3++ON699139bWvfU0zZszQRx99FOulAQCAGDMmiFavXq25c+fqG9/4hkaOHKm1a9fK7/dr3bp1sV4aAACIsbhYL6A7tLa26uDBg/qXf/mXqO1Tp07V3r17z/szLS0tamlpcZ5HIhFJUkNDQ9ctVFJTe3uXHh/ojbr63113+XPLZ7FeAtDjdPW/77PHt237gnNGBNEnn3yi9vZ2eTyeqO0ej0ehUOi8P1NUVKSnnnqqw3a/398lawRwAZYV6xUA6CLW9+d0y+s0NjbKusD/lxgRRGe5XK6o57Ztd9h21sqVK7VkyRLn+ZkzZ3Tq1CkNHjz4C38G146Ghgb5/X4dP35ciYmJsV4OgKuIf99msW1bjY2N8vl8F5wzIoiGDBmivn37drgaVFtb2+Gq0Vlut1tutztq2w033NBVS0QPlZiYyP9hAtco/n2b40JXhs4y4qbq/v37a8yYMdq9e3fU9t27d2v8+PExWhUAAOgpjLhCJElLlixRXl6exo4dq0AgoB/+8If66KOP9M1vfjPWSwMAADFmTBA99NBD+vTTT/Xd735XNTU1SktL02uvvaahQ4fGemnogdxut77zne90eNsUQO/Hv2+cj8u+2OfQAAAArnFG3EMEAABwIQQRAAAwHkEEAACMRxABAADjEUQw1uzZs+VyufTMM89Ebd+5cyffRg70QrZtKzMzU9OmTeuw78UXX5RlWfroo49isDL0BgQRjHbdddfp2WefVTgcjvVSAFwhl8ulH//4x9q/f7/Wr1/vbK+urtaKFSv0/PPP6+abb47hCtGTEUQwWmZmprxer4qKir5wZvv27br99tvldrv1pS99Sc8991w3rhDA5fD7/Xr++ee1bNkyVVdXy7ZtzZ07V5MnT9Zdd92le++9V9dff708Ho/y8vL0ySefOD/7yiuvKD09XfHx8Ro8eLAyMzN1+vTpGJ4NuhNBBKP17dtXhYWFeuGFF3TixIkO+w8ePKicnBw9/PDDOnTokAoKCvTEE0+opKSk+xcL4JLMmjVLkydP1j/+4z+quLhYhw8f1vPPP6+JEyfqzjvvVEVFhYLBoE6ePKmcnBxJUk1NjR555BHNmTNHVVVVevvtt/XAAw+Ir+ozB1/MCGPNnj1b9fX12rlzpwKBgEaNGqWXXnpJO3fu1P333y/btjVz5kzV1dVp165dzs8tX75cr776qo4cORLD1QO4kNraWqWlpenTTz/VK6+8onfffVf79+/X66+/7sycOHFCfr9fR48eVVNTk8aMGaM//OEP/AUDQ3GFCJD07LPPauPGjfrtb38btb2qqkoTJkyI2jZhwgQdO3ZM7e3t3blEAJchJSVF8+fP18iRI3X//ffr4MGDeuutt3T99dc7j9tuu02S9Pvf/1533HGHJk+erPT0dD344IPasGED9xYahiACJN19992aNm2aHnvssajttm13+MQZF1WB3iEuLk5xcX/5k51nzpzRfffdp8rKyqjHsWPHdPfdd6tv377avXu3fvnLX2rUqFF64YUXNGLECFVXV8f4LNBdjPnjrsDFPPPMM7rzzjs1fPhwZ9uoUaO0Z8+eqLm9e/dq+PDh6tu3b3cvEUAnfeUrX9H27dv1pS99yYmkc7lcLk2YMEETJkzQk08+qaFDh2rHjh1asmRJN68WscAVIuD/S09P18yZM/XCCy8425YuXao333xTTz/9tH73u99p48aNKi4u1rJly2K4UgCXa+HChTp16pQeeeQRlZeX68MPP9SuXbs0Z84ctbe3a//+/SosLFRFRYU++ugj/exnP1NdXZ1GjhwZ66WjmxBEwOc8/fTTUW+JfeUrX9FPf/pTbdu2TWlpaXryySf13e9+V7Nnz47dIgFcNp/Pp3feeUft7e2aNm2a0tLS9O1vf1uWZalPnz5KTEzUr371K917770aPny4/vVf/1XPPfecZsyYEeulo5vwKTMAAGA8rhABAADjEUQAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEQAAMB5BBAAAjEcQAbimuVwu7dy5M9bLANDDEUQAerVQKKRFixbplltukdvtlt/v13333ac333wz1ksD0Ivw1+4B9Fp/+MMfNGHCBN1www1atWqVRo8erba2Nr3++utauHCh3n///S553ba2NvXr169Ljg0gNrhCBKDXWrBggVwul8rLy/UP//APGj58uG6//XYtWbJEZWVlztwnn3yi+++/XwMGDFBqaqp+8YtfOPtKSkp0ww03RB13586dcrlczvOCggLdeeedevnll50rUbZty+Vy6Uc/+tEXHhtA70EQAeiVTp06pWAwqIULF2rgwIEd9n8+cp566inl5OTovffe07333quZM2fq1KlTl/V6H3zwgX76059q+/btqqysvKrHBhB7BBGAXumDDz6Qbdu67bbbLjo7e/ZsPfLII7r11ltVWFio06dPq7y8/LJer7W1VZs2bdKXv/xljR492rmCdDWODSD2CCIAvZJt25IU9dbWFxk9erTzvwcOHKiEhATV1tZe1usNHTpUycnJXXJsALFHEAHolVJTU+VyuVRVVXXR2XNvgHa5XDpz5owkqU+fPk5cndXW1tbhGOd7W+5ixwbQexBEAHqlpKQkTZs2Tf/+7/+u06dPd9hfX19/ScdJTk5WY2Nj1DE+f48QADMQRAB6rRdffFHt7e266667tH37dh07dkxVVVX6wQ9+oEAgcEnHyMjI0IABA/TYY4/pgw8+0NatW1VSUtK1CwfQ4xBEAHqtYcOG6Te/+Y2+/vWva+nSpUpLS9OUKVP05ptvat26dZd0jKSkJG3evFmvvfaa0tPT9V//9V8qKCjo2oUD6HFc9rlvngMAABiGK0QAAMB4BBEAADAeQQQAAIxHEAEAAOMRRAAAwHgEEQAAMB5BBAAAjEcQAQAA4xFEAADAeAQRAAAwHkEEAACM9/8AbZMky6nAQQQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=df['Churn'], palette = 'Set1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9349411d-9d53-4ada-a731-27f3021b06cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='tenure', ylabel='Count'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(df, x='tenure', hue='Churn', multiple='stack', palette = 'Set1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "352e5c5b-b09e-47b9-aa5a-c1e620f98413",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='MonthlyCharges', ylabel='Count'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(df, x='MonthlyCharges', hue='Churn', multiple='stack', palette = 'Set1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "06c67f23-cbd4-4cfe-8419-e8a5e5f85e54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='TotalCharges', ylabel='Count'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(df, x='TotalCharges', hue='Churn', multiple='stack', palette = 'Set1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "241b9fd3-e496-41ed-a4d9-800f2ac799f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='PaymentMethod', ylabel='Count'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x1800 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['SeniorCitizen'].replace({0: '< 65', 1:\">= 65\"} , inplace=True)\n",
    "sns.set_context('paper', font_scale=1.75)\n",
    "plt.figure(1,figsize=(30,18))\n",
    "plt.subplot(331)\n",
    "sns.histplot(df, x='gender', hue='Churn', multiple='dodge', palette = 'Set1')\n",
    "plt.subplot(332)\n",
    "sns.histplot(df, x='SeniorCitizen', hue='Churn', multiple='dodge', palette = 'Set1')\n",
    "plt.subplot(333)\n",
    "sns.histplot(df, x='Partner', hue='Churn', multiple='dodge', palette = 'Set1')\n",
    "plt.subplot(334)\n",
    "sns.histplot(df, x='Dependents', hue='Churn', multiple='dodge', palette = 'Set1')\n",
    "plt.subplot(335)\n",
    "sns.histplot(df, x='Contract', hue='Churn', multiple='dodge', palette = 'Set1')\n",
    "plt.subplot(336)\n",
    "sns.histplot(df, x='PaperlessBilling', hue='Churn', multiple='dodge', palette = 'Set1')\n",
    "plt.subplot(313)\n",
    "#plt.xticks(rotation=45)\n",
    "sns.histplot(df, x='PaymentMethod', hue='Churn', multiple='dodge', palette = 'Set1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "21be9905-6f0a-45cb-a510-1267700be865",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert all yes and no to 0's & 1's so our classifier can use this data.\n",
    "df['SeniorCitizen'].replace({'< 65': 0, \">= 65\": 1} , inplace=True)\n",
    "columns_to_convert = ['Partner', \n",
    "                      'Dependents', \n",
    "                      'PhoneService', \n",
    "                      'OnlineSecurity',\n",
    "                      'DeviceProtection',\n",
    "                      'TechSupport',\n",
    "                      'StreamingTV',\n",
    "                      'StreamingMovies',\n",
    "                      'PaperlessBilling', \n",
    "                      'Churn']\n",
    "\n",
    "for item in columns_to_convert:\n",
    "    df[item].replace(to_replace='Yes', value=1, inplace=True)\n",
    "    df[item].replace(to_replace='No',  value=0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dedd61e2-b99b-404a-92ae-82d39675f4c9",
   "metadata": {},
   "source": [
    "#### Feature Selection: Correlation matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "16151e18-5909-40d1-bba5-47df07e99de5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context('paper', font_scale=1)\n",
    "# compute the pair wise correlation for all columns  \n",
    "correlation_matrix = df.corr(numeric_only=True)\n",
    "# use the heatmap function from seaborn to plot the correlation matrix\n",
    "# Manipulate figsize in inches for \n",
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "# annot = True to print the values inside the square\n",
    "sns.heatmap(data=correlation_matrix, annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0c5a966-2f5f-4585-bbd3-c9ec41ab7910",
   "metadata": {},
   "source": [
    "#### Encode categorical data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c97c6a40-e0b5-4c5d-93ef-537eec476d7c",
   "metadata": {},
   "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>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>Churn</th>\n",
       "      <th>gender_Female</th>\n",
       "      <th>gender_Male</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingMovies_0</th>\n",
       "      <th>StreamingMovies_1</th>\n",
       "      <th>StreamingMovies_No internet service</th>\n",
       "      <th>Contract_Month-to-month</th>\n",
       "      <th>Contract_One year</th>\n",
       "      <th>Contract_Two year</th>\n",
       "      <th>PaymentMethod_Bank transfer (automatic)</th>\n",
       "      <th>PaymentMethod_Credit card (automatic)</th>\n",
       "      <th>PaymentMethod_Electronic check</th>\n",
       "      <th>PaymentMethod_Mailed check</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>29.85</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>56.95</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>53.85</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>42.30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>70.70</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SeniorCitizen  Partner  Dependents  tenure  PhoneService  PaperlessBilling  \\\n",
       "0              0        1           0       1             0                 1   \n",
       "1              0        0           0      34             1                 0   \n",
       "2              0        0           0       2             1                 1   \n",
       "3              0        0           0      45             0                 0   \n",
       "4              0        0           0       2             1                 1   \n",
       "\n",
       "   MonthlyCharges  Churn  gender_Female  gender_Male  ...  StreamingMovies_0  \\\n",
       "0           29.85      0              1            0  ...                  1   \n",
       "1           56.95      0              0            1  ...                  1   \n",
       "2           53.85      1              0            1  ...                  1   \n",
       "3           42.30      0              0            1  ...                  1   \n",
       "4           70.70      1              1            0  ...                  1   \n",
       "\n",
       "   StreamingMovies_1  StreamingMovies_No internet service  \\\n",
       "0                  0                                    0   \n",
       "1                  0                                    0   \n",
       "2                  0                                    0   \n",
       "3                  0                                    0   \n",
       "4                  0                                    0   \n",
       "\n",
       "   Contract_Month-to-month  Contract_One year  Contract_Two year  \\\n",
       "0                        1                  0                  0   \n",
       "1                        0                  1                  0   \n",
       "2                        1                  0                  0   \n",
       "3                        0                  1                  0   \n",
       "4                        1                  0                  0   \n",
       "\n",
       "   PaymentMethod_Bank transfer (automatic)  \\\n",
       "0                                        0   \n",
       "1                                        0   \n",
       "2                                        0   \n",
       "3                                        1   \n",
       "4                                        0   \n",
       "\n",
       "   PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
       "0                                      0                               1   \n",
       "1                                      0                               0   \n",
       "2                                      0                               0   \n",
       "3                                      0                               0   \n",
       "4                                      0                               1   \n",
       "\n",
       "   PaymentMethod_Mailed check  \n",
       "0                           0  \n",
       "1                           1  \n",
       "2                           1  \n",
       "3                           0  \n",
       "4                           0  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove customerID and TotalCharges\n",
    "try:\n",
    "    del df['customerID'] # not needed in analysis (it will lead to feature explosion in one hot encoding)\n",
    "    del df['TotalCharges'] # highly correlated with tenure and MonthlyCharges\n",
    "except:\n",
    "    print(\"already removed customerID and TotalCharges\")\n",
    "\n",
    "# Use one-hot encoding to convert categorical data to binary (0 or 1)\n",
    "df_dummies = pd.get_dummies(df)\n",
    "df_dummies.fillna(value=0, inplace=True)\n",
    "df_dummies.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b2597fb-b865-4a5b-b8a5-b660b062c36a",
   "metadata": {},
   "source": [
    "#### Extract features and target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d8529b14-ea93-462f-aa50-2cc2c0f6c27d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract Features and target variables\n",
    "X = df_dummies.loc[:,[i for i in df_dummies.columns if i != 'Churn']].values # Feature Variables\n",
    "y = df_dummies.loc[:,'Churn'].values # Feature Variable"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6ee2539-618c-4fe1-bac0-91d9d8ef85e8",
   "metadata": {},
   "source": [
    "#### Feature Selection: Forward Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f3802265-26e4-481c-abd4-ef56064c7d37",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "best combination (ACC: 0.799): (0, 3, 4, 5, 9, 10, 11, 13, 14, 15, 17, 18, 19, 20, 23, 30, 31, 33, 38)\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 1000x1000 with 1 Axes>,\n",
       " <Axes: xlabel='Number of Features', ylabel='Performance'>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.linear_model  import LogisticRegression\n",
    "from mlxtend.feature_selection import SequentialFeatureSelector as SFS\n",
    "from mlxtend.plotting import plot_sequential_feature_selection as plot_sfs\n",
    "\n",
    "log = LogisticRegression(max_iter=1000)\n",
    "\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.metrics import make_scorer\n",
    "f1_weighted = make_scorer(f1_score, average='weighted')\n",
    "\n",
    "sfs_range = SFS(estimator=log, \n",
    "           k_features=(15, 40),\n",
    "           forward=True, \n",
    "           floating=False, \n",
    "           scoring=f1_weighted,\n",
    "           cv=5)\n",
    "\n",
    "sfs_range = sfs_range.fit(X, y)\n",
    "\n",
    "print('best combination (ACC: %.3f): %s\\n' % (sfs_range.k_score_, sfs_range.k_feature_idx_))\n",
    "# print('all subsets:\\n', sfs_range.subsets_)\n",
    "plt.rcParams[\"figure.figsize\"] = (10,10)\n",
    "plot_sfs(sfs_range.get_metric_dict(), kind='std_err')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0cfda098-faf3-499c-9e98-ddc447da9972",
   "metadata": {},
   "outputs": [],
   "source": [
    "# keep 15 most important features that maximize the accuracy\n",
    "# Generate the new subsets based on the selected features\n",
    "# Note that the transform call is equivalent to\n",
    "# X[:, sfs_range.k_feature_idx_]\n",
    "\n",
    "X_sfs = sfs_range.transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b04ca99b-c5d2-45ff-8706-8187debb4245",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 5625 samples in the training set and 1407 samples in the test set\n"
     ]
    }
   ],
   "source": [
    "#Dividing data into test & train splitting 80% data for training anf 20% for test\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_sfs, y, test_size=0.20, random_state = 5)\n",
    "print('There are {} samples in the training set and {} samples in the test set'.format(X_train.shape[0], X_test.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3432635c-2906-46f0-b50f-9222fdd79992",
   "metadata": {},
   "source": [
    "### Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bb14479-9627-4cd6-ae1a-5a05a32d22c5",
   "metadata": {},
   "source": [
    "#### We will run all classifiers to have an initial feeling of the performance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e462738-3630-4eeb-8a78-4bb07ed9ad22",
   "metadata": {},
   "source": [
    "##### Defining function for Confusion Matrix , Precision, Recall and F1 Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b74bbc9c-1f0e-4932-9820-6707cfca43f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating function for Confusion Matrix , Precsion, Recall and F1 Score\n",
    "def plot_confusion_matrix(classifier, y_test, y_pred_test):\n",
    "    cm = confusion_matrix(y_test, y_pred_test)\n",
    "    \n",
    "    print(\"\\n\",classifier,\"\\n\")\n",
    "    plt.clf()\n",
    "    plt.imshow(cm, interpolation='nearest', cmap='RdBu')\n",
    "    classNames = ['Churn-No','Churn-Yes']\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    tick_marks = np.arange(len(classNames))\n",
    "    plt.xticks(tick_marks, classNames, rotation=45)\n",
    "    plt.yticks(tick_marks, classNames)\n",
    "    s = [['TN','FP'], ['FN', 'TP']]\n",
    "    \n",
    "    for i in range(2):\n",
    "        for j in range(2):\n",
    "            plt.text(j,i, str(s[i][j])+\" = \"+str(cm[i][j]), \n",
    "                     horizontalalignment='center', color='White')\n",
    "    \n",
    "    plt.show()\n",
    "        \n",
    "    tn, fp, fn, tp = cm.ravel()\n",
    "\n",
    "    recall = tp / (tp + fn)\n",
    "    precision = tp / (tp + fp)\n",
    "    #F1 = 2*recall*precision/(recall+precision)\n",
    "    F1 = f1_score(y_test, y_pred_test, average='weighted')\n",
    "\n",
    "    print('Recall={0:0.3f}'.format(recall),'\\nPrecision={0:0.3f}'.format(precision))\n",
    "    print('F1={0:0.3f}'.format(F1))\n",
    "    return;"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d25e351-ae9a-4fdd-b1b8-95bec5f3aac8",
   "metadata": {},
   "source": [
    "##### Defining function for Precision Recall Curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "553ed428-cfff-4c8c-8fcb-93168c34964e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import average_precision_score, precision_recall_curve\n",
    "def plot_prec_rec_curve(classifier, y_test, y_pred_score):\n",
    "    precision, recall, _ = precision_recall_curve(y_test, y_pred_score)\n",
    "    average_precision = average_precision_score(y_test, y_pred_score)\n",
    "\n",
    "    print('Average precision-recall score: {0:0.3f}'.format(\n",
    "          average_precision))\n",
    "\n",
    "    plt.plot(recall, precision, label='area = %0.3f' % average_precision, color=\"green\")\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    plt.xlabel('Recall')\n",
    "    plt.ylabel('Precision')\n",
    "    plt.title('Precision Recall Curve')\n",
    "    plt.legend(loc=\"best\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18557275-2adb-455d-b529-5a59c3b6fad1",
   "metadata": {},
   "source": [
    "#### Master Classification Engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "98ae5861-0d1c-41a4-8875-e8ada6f191e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " LogisticRegression \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall=0.554 \n",
      "Precision=0.689\n",
      "F1=0.791\n",
      "Average precision-recall score: 0.648\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " KNeighborsClassifier \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall=0.549 \n",
      "Precision=0.622\n",
      "F1=0.768\n",
      "Average precision-recall score: 0.575\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " GaussianNB \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall=0.880 \n",
      "Precision=0.493\n",
      "F1=0.716\n",
      "Average precision-recall score: 0.610\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " SVC \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall=0.429 \n",
      "Precision=0.681\n",
      "F1=0.759\n",
      "Average precision-recall score: 0.647\n"
     ]
    },
    {
     "data": {
      "image/png": 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uVAwnFhAQgBUrViAxMRF2dnZFxuucOXMmFi9ejJiYGLi5uRXb95w5czBnzpxyH19WVhbq1KmjmDYxMQEAZGZmFpkPAElJSQAKgzA8PBy5ubno378/li5disDAQOTl5WHy5MnYtm3bW7/CtHnzZowYMUJlo79UlKhJNGjQIABAeHj4G8N03759cHBwUPyBmD17NlavXo2zZ8+ie/fuxdqnpKQgJSWl2PyYmBgAwLLzy2CZYvnG2ga0GIAeTXuU+ViIiFRly5YtWLVqFe7duwegMKj+/Xdk/fr1i4TMvXv3MHz48CIvJdDQ0MCDBw9gZ2eHlStXYtOmTUhOToZEIsGLFy9U/rCOkZERXrx4oZh+3SOVSqXF2hoYGAAo/LvczMwMQOGl6NWrVyMwMBDffPMNvLy84Orq+sZ9Pn36FIcOHcKFCxdUdRgVVi26df+9fKCpqQlnZ2dERUWVGKbBwcEIDAwsdXuh0aHA8zfv82ryVYYpUS1R1h6jOty/fx8TJkzAiRMn4O7uDk1NTbi6uhZ56cB/3+RjZ2eHDRs2wMPDo9j2zp8/jyVLluD06dNwdnaGhoYGTE1NS32JwZIlS7BkyZJS64uOjoadnV2x+c7OzoiIiEDnzp0BFHaS6tevX6xXCgAODg7Q1dUttdd56tQphIeHY/v27QAKg/natWu4ePEitmzZomi3detWODg4oF27dqXWqy7VIkyzsrJgampaZJ6JiQkyMzNLbD9x4kT4+PgUm/96ZPUTo0+gVetWpe7PfbM7XuaXfD+BiKgyZWdnAwAsLQuvnm3ZsgVRUVFvXOfTTz/FvHnzsGXLFjRt2hTp6ek4fvw4hg0bhszMTGhpacHCwgIymQwrVqwo0oP8r7lz52Lu3Lnlrnvs2LFYsWIF+vTpA0NDQyxevLjUh4IMDAwwcuRIrFixAm5ubsjLy8P333+v+Hs7NDQUeXl5ivZDhw7FgAED4OfnV2Q7v/zyi+gPHr1WLcL0v5cPgMJ/qZR0+QAAbGxsYGNjU+r2TPVNYWlY+mVeQx1DZOaVHNRERJXJyckJX3zxBdzd3aGhoYHRo0crenulmTp1KiQSCfr164eHDx/CxMQE3t7eGDZsGHr27Il+/fqhRYsWMDQ0xPTp09GgQQOV1z1hwgTcv38fbm5uyM/Px4gRIzB//nzF8t69e+O9995TBPX333+PTz/9FA0aNICRkRFGjBiBL7/8EsD//UPiNV1dXZiYmBR5qvf69eu4ffs2PvzwQ5UfS0VIhCowmF9AQABu376NnTt3lrh848aN2LRpEy5fvgyg8LFqGxsb7Nixo8TLvKW5ceMG3NzccP36dbRp06bUdp1+7oSkjCQ8mPGg1DZEVD0VFBTgzp07cHBwgKamptjlUCUr7fdd1jwoK1G/GiOTyZCbmwuZTAa5XI7c3NwSv4A8aNAgxMbG4rfffkNeXh5WrFgBqVSKrl27Vkpdelp6yJXlvr0hERERRA7TxYsXQ19fH19//TVCQ0Ohr6+vuCZuZGSE8+fPAwDMzc3x+++/Y/HixTAxMcG+ffvwxx9/VNrXYvS09JBXkPf2hkRERBD5nmlAQAACAgJKXJaVlVVk2sPDQ20vamDPlIiIyoOvEyyBnpYeZHIZZHKZ2KUQEVE1wDAtgZ6WHgAgT8ZLvUQ1DQcFr13UNRg8w7QEepqFYcpLvUQ1j0QigUQiqTKjrVDlys3NhaamZrEXXahatfieqbq97pkyTIlqHolEAhMTE6SmpsLW1pY91RpKEATk5ubi4cOHsLKyqvT9MUxLoKulC4BhSlRTWVlZ4f79+7h7967YpVAl0tTUhJWVVbE36FUGhmkJ2DMlqtk0NDTQuHFjyOXyUt9RS9WbRCKp9Eu7/8YwLQHDlKh2UOdftlSz8U9SCRimRERUHgzTEjBMiYioPBimJWCYEhFReTBMS8AwJSKi8mCYloBhSkRE5cEwLQHDlIiIyoNhWgKGKRERlQfDtAQMUyIiKg+GaQkYpkREVB4M0xIwTImIqDwYpiVgmBIRUXkwTEvw7zA9f/88kjOTRa6IiIiqMoZpCV6HaURqBLqGdEWvbb3wquCVyFUREVFVxTAtweswPZ94HgIERD6OxLK/l4lcFRERVVUM0xLoauoqfu7coDOcrZyx+NxiRD2OErEqIiKqqhimJZBIJIqfP+/wOX72+RkFQgE++uMjyOQyESsjIqKqiGH6FgNaDEB72/aY0XEGriZfxepLq8UuiYiIqhiGaSlCBoTgyKgj0NHUAQAEegbC3sweC04vwN20uyJXR0REVQnDtBRjWo9BL/teimkDbQP87PMzcmW5mHBwAuSCXMTqiIioKmGYlkOXhl3wadtPce7+OQRfCxa7HCIiqiIYpuW0zGsZGhg3wOwTs/HgxQOxyyEioiqAYVpOxrrG+L7X98h6lYUtEVsqvJ2ox1Hos70PIh5FqLA6IiISA8O0Avo69EUd3TrYf3t/hdaPfxaPd9a/gyNxR3As/piKqyMiInVjmFaAjqYO+jn0w7Xka0jKSCrXurmyXAwNHVpkW0REVL0xTCvo/RbvAwAOxB4o13ozj85E2KMwdG/cvRKqIiIiMTBMK6iXfS/oauqW61LvrqhdWHdtHTwbeWJBlwWVWB0REakTw7SCjHSM4N3UG2funUF6Tvpb299Nuwu/g36oa1gXOwbvgKaGphqqJCIidWCYKuH95u+jQCjAoTuH3tguV5aLYXuGIetVFnYM3gFrI2s1VUhEROrAMFVC/+b9oSHRwO+xv7+x3fS/piP8UTj8u/qjW+Nu6imOiIjUhmGqBCtDK7g3cMdfcX8hJz+nxDY7o3Ziw/UN6N64O+Z3mV9suQChssskIqJKxjBVUo+mPfAy/yVupt4stuz1fVJrI2tsH7S9yH1SSwNLAEBKZoraaiUiosqhJXYB1V0D4wYAgNTs1CLzc/JzMDR0KF7mv8SBDw6grlHdIsubmDaBloYWbqfdVlutRERUOdgzVdLrkEzNKhqm049OR0RqBPy7+sOzsWex9bQ1tWFvZo/bTxmmRETVHcNUSa+fzH2U9Ugx77fI3xB8PRheTbww7715pa7bwqIF4p/F41XBq0qvk4iIKg/DVEl1DQt7pq/DNPZpLD4+9DGsjayxbeC2N36ftIV5CxQIBYh/Fq+WWomIqHIwTJVkaWgJCSRIzU5FTn4Ohu0Zhpf5L7Fj0I5i90n/q4VFCwAo86Xe57nPMXj3YHx/6Xul6yYiItVhmCpJS0MLloaWeJT1CPNOzcPN1JsI6BpQ4n3S/ypPmD59+RTdfu2GfTH7cOjum18SQURE6sWneVWgrmFd3H56G1eTr8LNxg1z35tbpvWaWzQHgLc+0ZucmQzvrd6IfhKtdK1ERKR67JmqgLWRNdJy0vCq4BUWeS4q83t3TfRMYG1kreiZlvTih/vP76PLL10Q/SQaK3usRB3dOiqtnYiIlMcwVYHX90Y72HZAL/te5Vq3hUULxDyJweJzi2G8zBh30u4olj3KeoRuW7ohIT0BG/puwIxOMwAAJxJOsJdKRFSFMExVoGGdhgCAIM8gSCSScq3bwrwFMl9lYsHpBZDJZTh//zwAICM3A7229UJCegKC+wVjYtuJhfPzMgAA4w+MV1n9t5/exqBdg3As/pjKtklEVJswTFVgZqeZODn6JHo07VHudV8/hPT68m1EagRyZbl4f9f7iEiNwGLPxfBz81O0d7NxAwBcenAJMrkMT18+hVyQF9lm/LN4LL+wHPkF+W/ctyAIWHNlDVyDXbH/9n4cjD1Y7vqJiIhhqhKm+qYVHg2md7Pe6GDbAYdHHYaxrjFupNzAqH2jcObeGUxpN6XYw0yXJlxSvAjiy+Nfwvpba3zz9zeK5RcSL6DDpg748sSXuJFyo9T9PnzxEL2298LUI1N5H5aISEkMU5E5mDvg0oRL6NygM1rVbYULSRewL2YfhrUchu97f1/ssrGWhhbetXsXALDq0ioUCAU4HHcYALD71m5039IdaTlpAIACoaDEff4V9xdcNrjgWPwxTHCdgPPjzlfiERIR1XwM0yrEro4dAMDZyhlb3t8CDUnJv55O9TtBT0sPDuYO6GDbAZcfXEbAmQAM3zMcZvpmGO0yusT1CuQF8D/tjz7b+0Aml2H/8P3Y6LMRUl1ppR0TEVFtwO+ZViEzOs6AhkQD3/X8DrpauqW2q6NXB+ETw2EjtUHwtWBcfngZgWcD4WzljD9H/om90XuxBVtwIfECMnIzoKWhBYlEgm8ufIMTCSfQxqYNQoeGoolpEzUeHRFRzcUwrULc6rlh68CtZWr7+oUPPZr2wOwTs9HSsiX+Hvc36ujVgaGOIQBg9onZxdab6DYRq3uthp6WXrFlW25uwbwu8xQv7yciorJhmFZzLtYuCJ8YjhYWLRS92Q9bfQgzfTNkv8pGgVAAmVyGAnkB7M3s4d3Uu9Rtvch7gfVX1yPQM1Bd5RMR1QgM0xrAxdqlyLS+tj6GOA0p8/rm+uZoYNwASS+S8DL/parLIyKq8fgAEkFbUxsnR59U/ExEROXDMCUiIlISw5SIiEhJDFMiIiIlMUypiP++55eIiN6OYUoAABupDQy0DXDm3hmxSyEiqnYYpgQAMNIxwrCWw3D54WVEpkYCKOylJmcmi1wZEVHVJ2qYPn/+HMOGDYNUKoWtrS3WrVtXatvdu3fDyckJUqkUDg4O2Lq1bG8KorLza1M41NvGGxvxLOcZ+v/WH7arbDnOKRHRW4j60oYpU6ZAJpMhOTkZcXFx8PLygqOjIzw9PYu0S0pKgq+vL/bu3Yt+/frh77//Rs+ePeHm5gYnJyeRqq95OtXvBCdLJ2yJ2IIDsQdwP+M+AGDVP6sqNFYrEVFtIVrPNDs7G6GhoVi8eDGkUilcXV0xduxYbN68uVjbxMREmJiYoH///pBIJHjvvffQtGlTREdHi1B5zSWRSODXxg8ZeRlIyUpBcL9gDHYcjKPxR3Hv+T28zH+Je8/viV0mEVGVI1rP9M6dOxAEoUjPsnXr1li1alWxth06dICDgwP279+PAQMG4OzZs0hNTYW7u3uJ205JSUFKSkqx+TExMao7gBrKr40fHmc/xmDHwXCr54bMvEzsjdmLv+L+wsp/ViIpIwnPvnwGA20DsUslIqoyRAvTrKwsGBsbF5lnYmKCzMzMYm21tLQwbtw4jB49Gjk5OdDQ0MCmTZtgY2NT4raDg4MRGMiXtVeEoY4hlnRfoph+PTj5p39+qpj34MUDOJg7lHvbd9Pu4tCdQ/jQ5UNYGFgoXywRURUhWpgaGRnhxYsXReZlZGRAKi0+UPXRo0cxa9YsHDt2DB06dEBMTAz69esHc3Nz9O3bt1j7iRMnwsfHp9j8mJgY+Pr6qu4gagFNiSYAoGGdhjDTN0PYozA0X9McBQsLSh28/L9kchlW/bMK/mf8kSvLRdC5ILhau+LBiwe48NEFWBpaVuYhEBFVOtHC1MHBARKJBDExMXB0dAQAhIeHw9nZuVjbyMhIuLu7o1OnTgCAli1bok+fPjhy5EiJYWpjY1Nqr5XKZ2jLocjOz8YnbT/B6kurEfYoDAAwYu8IaEo0sWPwjjeuH/4oHOMPjMeNlBtoZtYME90m4vvL3+P0vdMAgDkn5mCjz8YyBzMRUVUk2t9ghoaGGDJkCBYsWIDMzExEREQgJCQE48aNK9a2ffv2uHjxIq5evQoAiI2NxeHDh+Hi4lKsLalWPWk9zH1vLsz0zeDf1R/eTQrHQ919azcO3z2MoLNB2HRjU7H18mR5mHdyHtr+1BYRjyIwx30OIj6JwMzOMxE7JRaxU2Lh0cgDm8M3o+1PbfmyCCKq1kTtDqxduxYSiQQ2Njbo3bs3goKC0K1bNwCFl4HPnz8PAOjSpQuWLFmCUaNGQSqVwtvbGyNGjMD48ePFLL/W0dTQhLOVM/S09GBhYIGMvAz4n/HHD5d/KNIu6nEUOmzqgCV/L8E7dd/BVb+rWOq1FPra+gAKx1t1MHfAvmH7MLPTTEQ/iYbvPl5+J6LqSyIIgiB2Eepy48YNuLm54fr162jTpo3Y5VRLMrkMmXmZ8N3viyN3j0BLQwstLFrg5qc3IRfkWH1pNb46+RUK5AWY32U+5r03761jpHqEeCD6STQef/FYTUdBRLWdqvNA1Jc2UPWjpaEFU31TrOuzDs9ynuGDvR8AAJIzk/Hh/g9x6n+n0MysGbYO3IoO9TuIXC0RkXowTKlCGpo0REOThgCAh5kP0XpDazx5+QQft/kYq3qugqGOYbm2J5PLkJKZAktDS2hp/N8fy1uPb6GpWVPoaemVuq4gCJDJZW/tARMRVRaGKSntWc4z1NGtgz1D92Cw0+Byr6+rpYv03HTUW1UPEkhgbmCOuoZ1IRfkiHkagwVdFiDIM6jEdc/fP48Zx2bg3vN7uPjRRTQzb6bs4RARlRvDlJTS3rY9rI2sETIgBI1NG1doGyt7rMT+mP1IzU4t/GQV/vdO2h0AhWH9+r9m+mYAgPhn8fjyxJfYG7MX2hrakMllGLlvJK5MuKJ40QQRkbowTEkpWwcqP3qPs5UznK2Kf784OTMZtqts8eTlE4zYOwI7o3Zis89mRD+Jxg9XfsCrglcY2GIglnsvx6xjs/BH7B+QC3LFiyaIiNSFYUpV3u5buxU/f3TgIwBAG5s2WNVjFbo26goAb7ynSkRU2fjaGaqyjHSMoK2hjaamTRHo8X/vWv5lwC+46ndVEaQAkCvLBQC8v+t9dZdJRMSeKVVdxrrG+N+0/8HCwALamtro3KAzOth2gFS3+PubrQytAACH7hxSd5lEROyZUtVma2wLXS1daEg04NXEq8QgBYBve3yLJqZNoK+lr+YKiYgYplRDGOsao4VFC7HLIKJaimFKRESkJIYpERGRkhimRERESuLTvFSjyOQyTP5zMmykNhjecjikulJYG1mLXRYR1XAMU6pR8uX5WHdtHQBgwekFaGLaBFcmXIG5gbnIlRFRTcbLvFRjtLFuU+yJ3oT0BEw6PEmkioiotmCYUo2xqNsixEyOwZUJV/DXqL/g28oXQOE7fomIKhMv81KN0862HQCgp31P7IvZB6lOyS96ICJSFfZMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTIn+v8SMRIzePxpdfumCAnmB2OUQUTXCp3mpVkjKSMKqf1bBt5Uv3Oq54eGLh/gr7i/EpsXi846f44fLP2D1pdXIK8gDAGTnZ8NY11jkqomoumCYUo13PeU67FbbAQCOxh+FjqYOIlIjFMtXXFwBAGhVtxX0tfRx+eFlUeokouqLl3mpxnuc/Rjm+oWvE4x5GoOHmQ/h28oXgx0HK9ps9tmMGx/fgLOVs2Le/9L/h7G/j8WEAxOQmZdZ7v1mvcrCyosr8d0/3yl/EERUpbFnSjXa3HfnQl9bH1PaT8GFxAsw1DGEm40bNDU08argFY7GHUW3xt1gqGNYZL0vjn2BX8J/Qb48HwDwIu8Fdg/dXaZ9ZuZlYu3VtVj5z0o8ffkUADC903TVHhgRVSnsmVKNNq/LPMzoNAM6mjrwbOyJ9rbtoamhCQDQ0dRB/+b9iwUpAPx04ye4WLvg1OhTsKtjh7hncW/dV2ZeJpaeX4rG3zfGVye/gr6WPuzqFF5e9t7qjZTMFNUeHBFVGQxTon/p3KAzXOq64LfBv+HyhMvwbOwJLY03X8B5kfcCS84vQaPvG2Huqbkw1DFEcL9gxH0Wh0EtBgEATiScQM9tPdVxCEQkAl7mJfqXj1w/wkeuH5WpbU5+DtZcWYNlF5bhWc4zNKzTEMu6L8OY1mOgo6kDAFjmtQz1jetj1vFZiHwcWZmlE5GIGKZEb5GalYqE9ARsidiC0S6jIZPLEBIegoAzAXiY+RB2dezwjdc3GO0yWhGir+lq6WJm55nYf3s/bqTcwDvr34EEEjQxbYIhTkMUI9sQUfXGMCV6CxupDeKexWHlPythoG2A+afmIzYtFhYGFljdczU+afsJdLV037gNTQ1N5MhyEPU4CgAQ+TgSBUIBfFv5QhAESCQSdRwKEVUShinRW/z6/q9w3+yOm6k3MTR0KIx0jBDQNQAzOs2AVLdsw7sFdA1A2KMwvCp4hSfZT/DDlR/wKOsRxv8xHltvbsWPvX/ExLYTK/lIiKiyMEyJ3qJzg85wsnRC3LM4fNr2U8x9by6sDK3KtQ3Pxp7wbOypmF57dS2uJV/DteRrAIA7aXdUWjMRqRfDlKgMjn94HBJIYCO1Ucn2BjkOwou8FxjhPAK++3nflKi6Y5gSlUE9aT2Vbm/H4B0AgAcvHgAAjsQdwaR2k9DUrKlK90NE6sHvmRKJqJ60Hj5t+ylinsbA/kd7HI07KnZJRFQBDFMiEWlINPB1t68V06P2jcLz3OfiFUREFcIwJRKZqb4prvkVPoiUlpOGhacXilwREZUXw5SoCmhj0wZT208FAPx45UecTDgpckVEVB4MU6IqQCKR4IfeP2BN7zUAgGF7hiE1K1XkqoiorBimRFXI+DbjMbzlcDzLeYZV/6wSuxwiKiOGKVEVoqelhz7N+gAAll9cjhMJJwAAFxIvYMDOARgaOhQyuQx7o/di963deFXwSsxyiej/4/dMiaoY7ybe//fzVm/Ym9kXGU/1WvI13Ht+DwBgY2SDH3r/gCFOQ9RdJhH9C3umRFWMjdQG8oVyDGwxEAAQ9ywO41qPg2ejwtcRZr3KQpBHEJZ1X4YnL59g3dV1YpZLRGDPlKhKkkgkCO4XjG6Nu2FA8wFoUKcB4p7F4erDqxjQYgAMtA0AAF+d/Aqn753G9eTrcKvnhqSMJFgbWUNbU1vkIyCqXdgzJaqiLA0tMaX9FDSo0wAAYG9mjxHvjFAEKQCY6JkAAEb/Phrvbn4Xdqvt8OOVHwEAt5/eht8BP0gCJZj+13QUyAvUfgxEtQV7pkTVWOjQUHht9UL0k2hoSAr/bXws/hhO/e8U/rz7p6Ld6surMbTlUHRu0FmsUolqNPZMiaqx7k264xuvb7CgywJc/OgiAOBo/FEcvnsYA1sMxFHfo3C0cAQATDgwAZGpkYh9Gouph6dizok5YpZOVKOwZ0pUzc12nw0AkMllGOw4GDZGNvi84+eKEWhmdZ6F8QfGI+ZpDFptaFVk3aXdl0IikQAAMnIzEBIeguUXl0NfSx87h+xE23ptFW0L5AXIK8grcpmZiAoxTIlqCC0NLewZtqfY/A+cP8CDFw/gf8YfANC3WV/cTL2JpBdJ0AjSQEDXAKRmp2JLxBZk52cr1vPa4oXezXojKSMJSS+SkJiRCABwsnTClQlXYKhjqJ4DI6oGJIIgCGIXoS43btyAm5sbrl+/jjZt2ohdDpHayeQyaGloITEjES3WtECOLEexzNXaFVPbT4WZvhkeZj7Elye+RNarLFgaWKJBnQaITI1EvjwfQOHQcQmfJUBXS1esQyFSiqrzgD1TolpES6Pwf3m7Ona4+elNzD05F3paevik7SfoVL+T4pIvAIxtPRYSSKCvrQ8AkAtyBJwJwKJzi5CcmQzn9c6InhTNr+EQgWFKVGvZm9lj99DdpS7/771RDYkG/Lv6I0+Wh+UXlyPuWRzcfnJD2MQwaGpoVna5RFUan+YlojLT1NDE192/xuzOhQ89RT6OxMLTC/kWJqr1GKZEVC5aGlpY6rUUI5xHAACW/L0EUw5PQS16/IKoGIYpEZWbhkQDn7T9BMNbDkdz8+YQIKD5muZ4kfdC7NKIRMEwJaIK6dKwC3YO2YnJ7SYDAO4+uwvvrd5vWYuoZmKYEpFSpnaYik39NwEAIlMjRa6GSBwMUyJS2vg249HBtgPMDczFLoVIFAxTIiIiJTFMiUhlnr58Crvv7DD5z8lil0KkVgxTIlIJIx0j5MpykfQiCeuurcP5++fFLolIbUQN0+fPn2PYsGGQSqWwtbXFunWlf/E7NzcX06ZNg5WVFYyNjeHm5obMzEw1VktEbxLcLxinRp+CvZk9AGDKkSmYe3IuZh6diQE7B+BEwgmRKySqPKK+TnDKlCmQyWRITk5GXFwcvLy84OjoCE9Pz2JtP/nkE2RnZyMyMhKWlpaIjIyEjo6OCFUTUUmamjVFU7OmCB0aCtdgV9xMvYmbqTcVy68lX8Ptybch1ZWKWCVR5RAtTLOzsxEaGoqwsDBIpVK4urpi7Nix2Lx5c7EwvXPnDvbt24fExESYmJgAAFxcXESomojeprV1a3z17ldIepGEnPwcdGnYBbmyXHx54kssOrcIy72Xi10ikcqJFqZ37tyBIAhwcnJSzGvdujVWrVpVrO3ly5fRsGFDBAYGYuvWrbC0tMT06dPx8ccfl7jtlJQUpKSkFJsfExOjugMgolIt6b6kyHSBvAC7b+3Gd5e+w9jWY+Fk6VTKmkTVk2hhmpWVBWNj4yLzTExMSrwPmpSUhKioKPj4+ODhw4e4efMmvL290axZsxIvCQcHByMwMLDSaiei8tHU0MS6vuvQcVNHTDk8BSdHnywy3BtRdSfaA0hGRkZ48aLoezwzMjIglRa/n2JgYABNTU34+/tDV1cX7dq1w9ChQ3H48OEStz1x4kRcv3692Gfbtm2VcixE9HbtbdtjQpsJOH3vNHbd2iV2OUQqVeGe6Z9//omzZ8/i8ePHkMvlRZZt2bLlres7ODhAIpEgJiYGjo6OAIDw8HA4OzsXa9uqVaty1WZjYwMbG5tyrUNElW9J9yXYG7MX049Ox4XECxAg4Nse30JPS0/s0oiUUqGe6ZdffolBgwbh5s3CJ/U0NTWLfMrC0NAQQ4YMwYIFC5CZmYmIiAiEhIRg3Lhxxdp26dIFTZo0wddffw2ZTIawsDDs2bMH/fv3r0j5RCQSCwMLfOP1DR5lPcKaq2uw9upa6H+tj4zcDLFLI1JKhXqmmzdvRmhoKHx8fJTa+dq1a+Hn5wcbGxsYGxsjKCgI3bp1A1B4GfjIkSN47733oKWlhQMHDsDPzw/ffvst6tWrh1WrVqFLly5K7Z+I1G9Cmwl41+5dXHpwCeP+KPzH873n9+BizSf0qfqqUJhqa2ujefPmSu/cxMQEoaGhJS7LysoqMt2iRQucP883qhDVBC0sWqCFRQskZSRh4ZmFYpdDpLQKXeadN28eli1bhvz8fFXXQ0S1CJ/opZqiQj3TnTt34ubNmzh48CCaNWsGbW3tIsvPnTunkuKIqHaYc3IODo88DIlEgpf5L5Gek47bT29j3bV1iHochY39N6JLw8q9rSMIAsOdKqxCYerl5QUvLy9V10JEtUwd3ToAgL/i/kJodCiOxx/Hzls7kfWq6G2eoLNBOP7hcfyd+Dd+DvsZv0b8CgAInxhe5F5rgbwAZ++fRVhKGFxtXHEn7Q4kkMCtnhvyC/JhomeCJqZNcOnBJeTKcnH2/ll8e/Fb5MsLr7J94PwBQgaEQFdLV01ngGoKiSAIgthFqMuNGzfg5uaG69evo02bNmKXQ1Trvcx/ie5buuPSg0uKeW1s2hQONK5vDlcbVwzePbjU9Xvb98YnbT9BaHQott3cBkNtQ2TnZytV04EPDqB/c35ToKZTdR5U+HumgiDgr7/+QmxsLADA0dERPXr04GUSIiozA20DzOo0C7OOz0K/Zv0wvs14tLZuXaTNgOYD8EfsH9DV1MXU9lMxpvUY3H9+H/1+64cjcUdwJO6Ioq2GRAN9mvXB34l/w8nSCZPbTcaT7CdYeGYhejbtiYN3DsKujh183/GFhYEFnK2c0aBOA1gaWGL4nuE4EncEPjt90LNpT1x6cAm7huxCT/ueaj4rVB1VqGcaFxcHHx8f3L9/X/FUb2xsLBo3bow//vgDTZs2VXmhqsCeKVH1JBfkEAQBmhqF32PPk+Vh5rGZaGLaBLqauujepDt0NXXR0KQhNCQVe7Hbsfhj6LmteHCeGXMGp++dhqWBJSa356DnNUWV6JlOmjQJzZo1w4ULF2BqagoAePbsGcaOHYtJkybh6NGjShdGRPSahkQD+NdFL10tXazps0al+/Bq4oW/x/2NxIxENDFtgo4/dwQAePzqoWiTnZ+N2e6zVbpfqhkqFKZ///03rl27pghSADAzM8PSpUvRvn17lRVHRKQuGhINuNu5wx3uAIC9w/Zizok56N64O44nHEd8ejzmnJiD9rbtse3mNtx6cgureqxCpwadRK6cqoIKhalUKkViYmKR4dMAIDExscQX1RMRVTeDHAdhkOMgAEBOfg6c1zsjIT0Bnr/+30hVi84twuFRJQ+4QbVLhcJ0zJgxGDduHAICAtChQwcAwKVLlxAYGIixY8eqsj4iItHpa+tjgusE7Lq1C/0d+qOlVUuM2DsCR+KO4NNDn6K5RXM0NW0KHU0d/BX3F66nXMfmAZthb2YvdumkJhUK06VLl8LExAQBAQFITU0FANStWxfTpk3DF198odICiYiqgq/e+wpfvfeVYnraX9PwOPsxNlzfUGL79VfX4wv3L2BtZK2uEklESn/P9PWYpP8d6Lsq4tO8RKQqlx5cwo7IHbiTdgdxz+LwMPMhZnaaCamOFHNOzlG0O+Z7DBYGFnC1cRWxWvqvKvE0779VhxAlIlK1jvU7omP9jsXmv8h7gTP3z+CvuL8AAD229YAEEiROT0R94/rqLpPUpMxhamdnh7CwMJibm6NBgwZvfDlDYmKiSoojIqpujHWNcWTUEVxLvobhe4ZDLshx7/k9pOekM0xrsDKH6aJFi2BkZAQAWLx4caUVRERUE7St1xbxn8Uj4EwAAs8GotWGVqhrWBeLPBfBz81P7PJIxcocpmPGjCnxZyIiKl3Xhl0VP6dmp+LjQx/D1tgWfZr1EbEqUrUKvXfr8uXLCAsLU0yHhoaiX79+mDVrFnJyclRWHBFRdefZ2BPZc7Nx1Pco6knrAQAG7RokclWkahUK008++QT3798HANy5cwejR49Gw4YNceLECUyfPl2lBRIRVXcG2gbo0bQHLnx0AQCQV5BXatv8gnx1lUUqVKEwvXv3LlxcCscQ3LVrF3r16oW1a9di06ZN+OOPP1RaIBFRTdHIpJHi8u6aK2sgCALinsXhevJ1fHvxW7z3y3vQ+1oPa66o9r3DVPkq9NUYXV1d5ObmAgCOHz+O0aNHAwDMzc2RkZGhuuqIiGqYuoZ1AQBTj0zF1CNTiyzT0dSBXJAj5kkMBEHgkJbVSIXCtFu3bpg5cybc3d1x7do1hIaGAgCio6PRqFEjVdZHRFSjfN/re+TKcvFb1G8w1jVG9qtsjHYZjUGOg+Bo4Qj7H+2x7to6rLu2Dtoa2qgnrYdXBa9gbmAOezN7/H77d3g08sDnHT6HoY4hvJp4iX1IhAqGaXBwMObPn4/Lly9j165dqFu38F9aV69exciRI1VaIBFRTSLVlWLH4B3YMXhHsWUyuQxeTbxwIuEEACBfno/7GYXPp6RkpSDqcRQA4My9Mzhz7wx0NHWQMy+nwmO4kupUKEzNzMywbt26YvMDAgKUrYeIqNbS0tDC8Q+PAwDinsXBytAKUY+jkJiRqAja6CfRWHNlDaKfRCM2LRaCIBQZ65XEUeYwPXXqFLp06QItLS2cOnXqjW27deumdGFERLXZ6xFnOjfojM4NOivmWxtZo1vjbhi+Zzhi02KhtUgLvq18sXXgVrFKJZQjTL28vPDo0SNYWVnBy6v0a/QSiQQFBQUqKY6IiErm3sAdu2/tBgBsu7kNiRmJcLJwgmdjTwxrOUzk6mqfMl9ol8vlsLKyUvxc2odBSkRU+T7r8BkEfwGBHoEAgHP3z2HD9Q0Yvmc4JIES/H77d3ELrGWUHjWGiIjEs7DrQng38cbN1Js4de+Uorc6cNdANKzTEHuG7UF+QT7a2LSBrpauyNXWXBV6BGzKlClYu3Ztsflr167FtGnTlC6KiIjKrlODTpjYdiJ2DdmFnHk5aGTSCABwP+M+2m1sh86bO0Pvaz2cu38OBfICpOeki1twDVShMN27dy/c3d2LzX/33Xexe/dupYsiIqKK0dPSw/+m/Q83Pr6BetJ6RcZcnfTnJGgt0oLZcjOM3DsSBXLellOVCoXp8+fPoa+vX2y+np4enj9/rmxNRESkJFcbVzyc8RD/jP8H1z++DgC49eSWYvlvUb9Ba5EWRu0bBbkgF6vMGqNCYeri4oLt27cXm79161Y4OzsrXRQREamOq7Ur/hn/D1JmpiBvfh4mt5usWLYjcgeMlxqjyy9dCr+zShVSoQeQFi1ahH79+iE8PBweHh4AgDNnzuDYsWM4ePCgKusjIiIlSSSSIpd71/RZg6+7fY1lfy/DsgvLkJ2fjfOJ56ERpIFN/TdhfJvxIlZbPVWoZ+rt7Y2wsDCYmZlhx44d2L59O8zMzBAWFgZvb29V10hERCpWR68OgjyDkPBZAlZ4r1DMn36Uw2hWRIW/GuPk5ISQkBAVlkJEROqkramNxqaNMavzLEx0m4gmPzThe34rqMJnLTExEUuWLIGfnx+ePHkCoPBS7927d1VWHBERqYdUV4oWFi0g4Yt+K6RCYXr27Fk4OTnh7Nmz2LJlCzIzMwEAly9fxldffaXSAomIiKq6CoXp7Nmz8c033+Do0aPQ0dFRzO/evTv++ecflRVHRERUHVQoTKOiotC3b99i883MzJCWlqZ0UURERNVJhcLU2tq6xHuj586dQ5MmTZQuioiIqDqpUJhOmzYNkyZNwuHDhwEA0dHRWLt2LWbMmIEZM2aotEAiIlIPQRCQmp2Kpy+fil1KtVOhr8Z89tlnMDIywtSpU5GdnQ0fHx9YW1sjKCgIEyZMUHWNRESkBgIK34Bku8oWEZ9EoIVFC5Erqj7K3TOVyWT4448/4OPjg/j4eGRmZuLRo0dITk7GlClTKqNGIiJSg6/eLfw2xquCV/joj49ErqZ6KXeYamlpYcSIEcjKygIAGBoaKgYNJyKi6qufQz8I/gKamDZBrixX7HKqlQrdM+3UqRNu3Lih6lqIiKgK4Isbyq9C90xHjhyJzz//HNHR0WjdujUMDAyKLO/WrZtKiiMiInEUCBzrtDwqFKZ+fn4AgIULFxZbJpFIUFDAXwIRUXWVI8tBfHo8Pjn0CTb02yB2OdVCuS/zJiQkYP369fjxxx8RHh4OuVxe5MMgJSKq3sa7Fg7BFvk4UuRKqo9yhemxY8fQsmVLzJo1C/Pnz4ebmxt+/vnnyqqNiIhEEOQZBANtA1xMuoiDsRyjuizKFaYLFizA2LFj8fz5c6Snp2PRokWYM2dOZdVGREQisTezBwCsv7Ze5Eqqh3KFaXR0NGbNmgVNTU0AwMyZM5GRkYHHjx9XSnFERCSO8+POAyh8Doberlxh+vLlSxgbGyumtbW1oaurq/jOKRER1QzGusbQ19LH4buH0W5jO+yJ3iN2SVVauZ7mFQQBy5Ytg6GhoWLeq1ev8N1338HU1FQxLygoSHUVEhGRKPo064O9MXtxLfkajsYdxRCnIWKXVGWVK0y7dOlS7GUNnTt3RlRUlGKalwSIiGqGPcP2IO1lGixWWIhdSpVXrjA9c+ZMJZVBRERVkaaGptglVAsVep0gERHVLum56RAEQewyqiyGKRERvdXemL1w+8kNT7Kf4HrydeyI3IE8WZ7YZVUZFXqdIBER1Q51dOtgsONg7I3Zi7BHYbD69v9GCRuFURjecjhW9VwFTYkmLA0toSGpnX00hikREZVKIpFgz7A92H1rN1b+sxJWhlbQ0dTBvph9AIBdt3Zh161dAAAdTR08//I59LX1xSxZFAxTIiJ6q2Eth2FYy2GK6QJ5AXZG7cT0o9Px5OUTAIWDiqfnptfKMK2d/XEiIlKKpoYmRrUahcdfPIbgL2Bah2kAgBF7R6DXtl54lvNM5ArVi2FKRERKM9UrfHHPufvncDT+KNptbCdyRerFMCUiIqXN6jwLl8ZfwqERhwAACekJIlekXgxTIiJSmqGOITrU74C+Dn3Ry74XACAzL1PkqtSHYUpERCr1+uUOXUO6ilyJ+ogaps+fP8ewYcMglUpha2uLdevWvXWdkJAQSCQSbNiwQQ0VEhFReU1uNxkAEJ8eL3Il6iPqV2OmTJkCmUyG5ORkxMXFwcvLC46OjvD09CyxfVpaGpYtWwZnZ2c1V0pERGXVv3l/uDdwZ5iqQ3Z2NkJDQxEWFgapVApXV1eMHTsWmzdvLjVMZ86ciVmzZmHbtm1v3HZKSgpSUlKKzY+JiVFJ7URERP8mWpjeuXMHgiDAyclJMa9169ZYtWpVie3PnDmDO3fu4JdffnlrmAYHByMwMFCl9RIREZVGtDDNysqCsbFxkXkmJibIzCz+9FdeXh4mT56Mbdu2lWm81IkTJ8LHx6fY/JiYGPj6+la8aCIiKhO5IMejrEdIzkxGPWk9scupdKKFqZGREV68eFFkXkZGBqRSabG233zzDby8vODq6lqmbdvY2MDGxkYldRIRUflpaRTGy8BdA3F5wmWRq6l8oj3N6+DgAIlEUuQ+Znh4eIkPF506dQq//vorLCwsYGFhgQsXLmDWrFkYPXq0OksmIqIyCvAIAABceXgF3/z9jbjFqIFoYWpoaIghQ4ZgwYIFyMzMREREBEJCQjBu3LhibUNDQxEVFYXw8HCEh4ejbdu2mD9/Pr777jsRKiciorfp1rgbPmz1IQBgzsk5kARKcCz+mMhVVR5Rv2e6du1aSCQS2NjYoHfv3ggKCkK3bt0AFF4GPn/+PADA0tIS9evXV3x0dXVhYmICc3NzMcsnIqI32DJwCz5w/kAx/eOVH0WspnKJ+j1TExMThIaGlrgsKyur1PXOnDlTSRUREZEq/Tb4N6zrsw5my83ELqVS8XWCRERUqUz1TaGnpSd2GZWKYUpERGrx+p29NRHDlIiIKl2uLBd/3v0T2ou0cevxLbHLUTmGKRERVTq/Nn4AAJlchjVX1ohcjeoxTImIqNL91P8nXBp/CQCw4foGRKZGilyRajFMiYhILVysXRQ//xrxq4iVqB7DlIiI1EJPSw8XP7oIoOY9jMQwJSIitbE1tgUArLq0ClsitiAnP0fkilSDYUpERGpjqmeq+HnM72NgsMQAJxJO4FHWI0Q8ihCxMuWI+gYkIiKqXaS6Uryc+xKzj8/GmquFT/UO3j0YL/L+bxSx2Z1nw8rQCjM7zxSrzHJjmBIRkVrpa+vjxz4/Ynqn6Xhn/TuwMrRCY5PGiEgt7Jkuv7gcQOGYqMOdh8PK0ApyQQ59Lf0yjWktBoYpERGJoolpE2R+lQkNSeEdx6cvn2JX1C6c/N9J7L+9H7NPzMbsE7MV7fs064M/R/4pVrlvxHumREQkmtdBCgAWBhaY3H4yfuj9Aya6TVQMMP7a4buHIQmUYOP1jeou860YpkREVKXUN66PDf02IH9BPgR/AYK/gJHvjFQsX3dtXZX7ag3DlIiIqrztg7ajYGEBdDV1Ef4oHBpBGgh/FC52WQoMUyIiqhY0JBoI8gxSTLsGu+JC4gURK/o/DFMiIqo2ZrvPRvxn8YrprTe3iljN/2GYEhFRtdLEtAkSP08sMk8uyHE37S6239yOM/fOqP2eKr8aQ0RE1Y6hjiEA4My9M+ga0hVhKWHIfJWpWH5+3Hm8a/eu2uphz5SIiKodPS096GvpIzYtFuGPwtHGpg0muk1ULL///L5a62HPlIiIqh0DbQNEfhoJAQKamDZRfF+1U/1OGPvHWPju90WH+h1gb2avlnrYMyUiomqpqVlT2JvZF3nxg3dTb8XPLhtccOvxLbXUwjAlIqIao560Hn4f/jsA4GX+Szivd8bhu4crfb8MUyIiqlEGtBiA8Inhium+O/oiMSOx9BVUgGFKREQ1jou1Cx5Mf6CYbri6Ifps71Np+2OYEhFRjWRrbItrftegraENADgSd6TS9sUwJSKiGsutnhteLXiFgS0GAgDupN2plP0wTImIqMbT0dQBAHht8aqU7TNMiYioxpvfZT4AIOlFEgbtGoRNNzapdPsMUyIiqvGcrZwxtvVYAMD+2/ux/up6lW6fYUpERLXCT/1+wpFRR/BTv59gomei0m0zTImIqFbQ1tRGL/te8HPzg56Wnkq3zTAlIiJSEsOUiIhISQxTIiKqdSa2nfj2RuXAMCUiolrHp7mPSrfHMCUiIlISw5SIiEhJDFMiIiIlMUyJiIiUxDAlIiJSEsOUiIhISQxTIiIiJTFMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCUiIlISw5SIiEhJDFMiIiIlMUyJiIiUxDAlIiJSEsOUiIhISQxTIiIiJTFMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCUiIlISw5SIiEhJDFMiIiIliRqmz58/x7BhwyCVSmFra4t169aV2O7SpUvo2bMnzM3NYW5ujr59++Lu3btqrpaIiKhkoobplClTIJPJkJycjEOHDmHBggU4ffp0sXbp6en46KOPkJCQgJSUFDg7O8PHx0eEiomIiIrTEmvH2dnZCA0NRVhYGKRSKVxdXTF27Fhs3rwZnp6eRdr27t27yPTMmTOxfPlypKWlwdzcXJ1lExERFSNamN65cweCIMDJyUkxr3Xr1li1atVb1z179iysra1LDdKUlBSkpKQUmx8TE1PxgomIiEohWphmZWXB2Ni4yDwTExNkZma+cb2EhARMmTIFP/74Y6ltgoODERgYqJI6iYiI3ka0MDUyMsKLFy+KzMvIyIBUKi11nQcPHsDb2xtz5szBsGHDSm03ceLEEu+pxsTEwNfXt+JFExERlUC0MHVwcIBEIkFMTAwcHR0BAOHh4XB2di6x/cOHD+Hp6Qk/Pz9Mnz79jdu2sbGBjY2NymsmIiIqiWhP8xoaGmLIkCFYsGABMjMzERERgZCQEIwbN65Y2+TkZHh4eMDX1xdz5swRoVoiIqLSifrVmLVr10IikcDGxga9e/dGUFAQunXrBqDwMvD58+cBABs3bkRcXBxWrFgBIyMjxScxMVHM8omIiACIeJkXKHzgKDQ0tMRlWVlZip/9/f3h7++vrrKIiIjKha8TJCIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCUiIlISw5SIiEhJDFMiIiIlMUyJiIiUxDAlIiJSEsOUiIhISQxTIiIiJTFMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCUiIlISw5SIiEhJDFMiIiIlMUyJiIiUxDAlIiJSEsOUiIhISQxTIiIiJTFMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCUiIlISw5SIiEhJDFMiIiIlMUyJiIiUxDAlIiJSEsOUiIhISQxTIiIiJTFMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCUiIlISw5SIiEhJDFMiIiIlMUyJiIiUxDAlIiJSEsOUiIhISQxTIiIiJTFMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCUiIlISw5SIiEhJDFMiIiIlMUyJiIiUxDAlIiJSEsOUiIhISQxTIiIiJTFMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiWJGqbPnz/HsGHDIJVKYWtri3Xr1pXa9uzZs3B2doaBgQE6duyIW7duqbFSIiKi0okaplOmTIFMJkNycjIOHTqEBQsW4PTp08XapaWlYcCAAfjqq6+Qnp6OAQMGYMCAAZDJZCJUTUREVJRoYZqdnY3Q0FAsXrwYUqkUrq6uGDt2LDZv3lys7b59++Dg4IBRo0ZBV1cXs2fPRmZmJs6ePStC5UREREVpibXjO3fuQBAEODk5Kea1bt0aq1atKtY2KioKLi4uimlNTU04OzsjKioK3bt3L9Y+JSUFKSkpxeaHh4cDAGJiYlRwBEREVF29zoGcnByVbE+0MM3KyoKxsXGReSYmJsjMzCyxrampaZnaAkBwcDACAwNL3bevr28FKiYiopomLCwM7u7uSm9HtDA1MjLCixcviszLyMiAVCpVqi0ATJw4ET4+PsXmX758GZMmTcLPP/+M1q1bV7z4WiYmJga+vr7Ytm0bHB0dxS6nWuA5qxiet/LjOauY8PBwjB8/XmXnTLQwdXBwgEQiQUxMjOJgwsPD4ezsXKyts7MzNm3apJiWy+WIjIzEV199VeK2bWxsYGNjU+q+W7dujTZt2ih5BLWPo6Mjz1s58ZxVDM9b+fGcVcx/r3pWlGgPIBkaGmLIkCFYsGABMjMzERERgZCQEIwbN65Y20GDBiE2Nha//fYb8vLysGLFCkilUnTt2lWEyomIiIoS9asxa9euhUQigY2NDXr37o2goCB069YNQOGl3fPnzwMAzM3N8fvvv2Px4sUwMTHBvn378Mcff0BLS7SONRERkYKoaWRiYoLQ0NASl2VlZRWZ9vDw4IsaiIioSuLrBImIiJRUq8LUxsYG/v7+b3w4iYrjeSs/nrOK4XkrP56zilH1eZMIgiCoZEtERES1VK3qmRIREVUGhikREZGSGKZERERKYpgSEREpqUaGKQcdL7+ynrNLly6hZ8+eMDc3h7m5Ofr27Yu7d++qudqqozx/1l4LCQmBRCLBhg0b1FBh1VOec5abm4tp06bBysoKxsbGcHNzK3WAi5quPOdt9+7dcHJyglQqhYODA7Zu3arGSquONWvWoG3bttDV1cUHH3zwxrZKZ4FQA40aNUoYOHCg8OLFC+HGjRuCmZmZcOrUqWLtnj59KtSpU0fYtm2bkJubKyxZskRo2rSpkJ+fL0LV4irrOTt8+LCwc+dO4fnz50JeXp4we/ZsoUWLFiJUXDWU9by99vTpU6F58+aCs7OzsH79ejVWWnWU55yNGTNGGDJkiPDo0SOhoKBACA8PF3Jzc9VccdVQ1vOWmJgoaGtrCwcOHBDkcrlw7tw5QV9fX7h165YIVYtr7969wv79+4XJkycLw4cPL7WdKrKgxoVpVlaWoKOjU+QPzowZMwRfX99ibX/66SehXbt2immZTCZYWVkJJ06cUEutVUV5ztl/paamCgCEp0+fVmaJVVJFztuYMWOEjRs3Cl27dq2VYVqecxYbGytIpVIhPT1djRVWTeU5b3///bdgaWlZZJ6zs7MQGhpa6XVWVf7+/m8MU1VkQY27zFvaoONRUVHF2r5p0PHapDzn7L/Onj0La2trmJubV2aJVVJ5z9uZM2dw584djB8/Xl0lVjnlOWeXL19Gw4YNERgYCAsLCzg6OuKnn35SZ7lVRnnOW4cOHeDg4ID9+/dDLpfj9OnTSE1NVcmYnTWVKrKgxr0pvjIHHa+pynPO/i0hIQFTpkzBjz/+WJnlVVnlOW95eXmYPHkytm3bBolEoq4Sq5zynLOkpCRERUXBx8cHDx8+xM2bN+Ht7Y1mzZrB09NTXSVXCeU5b1paWhg3bhxGjx6NnJwcaGhoYNOmTXxD0huoIgtqXM+0Mgcdr6kqch4ePHgAb29vzJkzB8OGDavsEquk8py3b775Bl5eXnB1dVVXeVVSec6ZgYEBNDU14e/vD11dXbRr1w5Dhw7F4cOH1VVulVGe83b06FHMmjULx44dw6tXrxAWFgZ/f3/8+eef6iq32lFFFtS4MP33oOOvvWnQ8YiICMX060HHS2pbk5XnnAHAw4cP4enpCT8/P0yfPl1dZVY55Tlvp06dwq+//goLCwtYWFjgwoULmDVrFkaPHq3OkkVXnnPWqlUrdZZWpZXnvEVGRsLd3R2dOnWChoYGWrZsiT59+uDIkSPqLLlaUUkWVPSGblU2cuRIYfDgwcKLFy+E8PBwwdzcXDh58mSxdq+f4NqxY4eQm5srLFu2rNY+zVvWc/bw4UPB3t5eCAgIEKHKqqes5+3x48dCUlKS4tOxY0dh6dKltfLBrbKes/z8fKFZs2bCwoULhfz8fOHGjRuCiYmJcPbsWRGqFl9Zz9vZs2cFU1NT4cqVK4IgCMLt27eFRo0aCT/99JO6SxZdfn6+kJOTI8ybN08YOnSokJOTI7x69apYO1VkQY0M0/T0dGHIkCGCoaGhYGNjI6xdu1axzNDQUDh37pxi+vTp04KTk5Ogp6cntG/fXoiKihKjZNGV9ZwFBAQIAARDQ8Min/v374tVuqjK82ft32rr07yCUL5zFhMTI7z77ruCgYGBYG9vL2zevFmMkquE8py39evXC82aNROMjIyEBg0aCF999ZVQUFAgRtmi8vf3FwAU+YwZM0YQBNVnAUeNISIiUlKNu2dKRESkbgxTIiIiJTFMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCWiMgkICMC7776rmPbw8MD8+fNFrIio6mCYElUjHh4ekEgkkEgkMDQ0ROvWrREaGip2WUS1HsOUqJr5/PPPkZKSgqioKIwcORIjRowo8pJuIlI/hilRNWNoaAhra2s0btwYs2fPRp06dXDmzBkAwI0bN+Dh4QF9fX00atQI/v7+kMlkinUfP34MX19fmJmZwcjICO7u7oiPjwcAHDhwAB07doRUKkW9evUwadIkZGdni3GIRNUOw5SompLL5di3bx/S09Oho6ODtLQ0eHt7o0+fPoiMjERISAh27NiBlStXKtYZNGgQ4uPjcfDgQYSFhWHixImKsM3NzcW8efMQERGBnTt34vTp0wgMDBTr8IiqFb7onqga8fDwwMWLF6Gjo4O8vDzIZDI0aNAAN27cwLp163Dz5k3s2bNH0X7Hjh1YuHAh4uLicPr0afTq1QsJCQmwtbV967527tyJuXPnIiEhAUDhA0gnTpzA33//rajl3XffxeLFiyvnYImqES2xCyCi8nk9KHtycjJmzpyJoKAgWFhYIDIyEgcOHICRkZGibUFBAfLz8yGXyxEVFYVmzZqVGqTR0dGYN28erl+/jvT0dMhksiKXiImodAxTomrG1NQU9vb2sLe3x/bt2+Hu7o7IyEhkZWXhgw8+wMKFC4uto6GhgbddhPLx8UGrVq2wfft2WFlZ4dy5c/j4448r6zCIahSGKVE15uDgAA8PDyxevBguLi44ceIE7O3tS2z7zjvv4O7du0hOTka9evWKLHv69Cni4+OxZ88etG7dGgCwe/fuyi6fqMbgA0hE1dyUKVPw888/Y/LkyYiPj4efnx8iIiIQGxuL3bt3K+5penp6ol27dhg8eDAuXLiA+Ph4bN++HbGxsTA1NYWpqSk2btyIhIQE7Nq1C8HBwSIfGVH1wTAlqua6du0KBwcHrF69GufOnUNSUhLc3d3Rrl07fPvtt7Czs1O03bdvHxo1aoQ+ffrAxcUF69evh5aWFjQ1NbF9+3YcO3YMLVu2RHBwMJ/kJSoHPs1LRESkJPZMiYiIlMQwJSIiUhLDlIiISEkMUyIiIiUxTImIiJTEMCUiIlISw5SIiEhJDFMiIiIlMUyJiIiUxDAlIiJSEsOUiIhISQxTIiIiJf0/GZrF7mRO2K8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " DecisionTreeClassifier \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall=0.495 \n",
      "Precision=0.561\n",
      "F1=0.736\n",
      "Average precision-recall score: 0.431\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " RandomForestClassifier \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall=0.502 \n",
      "Precision=0.589\n",
      "F1=0.748\n",
      "Average precision-recall score: 0.598\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " SGDClassifier \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall=0.292 \n",
      "Precision=0.748\n",
      "F1=0.728\n",
      "Average precision-recall score: 0.626\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " AdaBoostClassifier \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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lSxo4cKD++9//3tPMdgAA0vJAJEuvXr00ZcoUjRs3TkWKFJGfn5/CwsLUvHnzu2771ltvycfHR35+fmrRooXatGmT5fU2bNhQFStWTLFs4MCBqlmzpipXrqzSpUurcOHCmjhxYpbXAgDIeRw+YQ1/27Ztmx5//HEmrCHHYsIacjKjJqwBAICMIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwxDeAAAYhvAGAMAwhDcAAIYhvAEAMAzhDQCAYQhvAAAMQ3gDAGAYwhsAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwxDeAAAYhvAGAMAwhDcAAIYhvAEAMAzhDQCAYQhvAAAMQ3gDAGAYwhsAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhnNPTyGq1pnuHuXJxPgAAQFZKV3g7OzvLYrGka4fJycn/qiAAAJC2dIX3unXrsroOAACQTukK79q1a2d1HQAAIJ3u6QL1li1b1KVLF9WvX18nT56UJC1evFhbtmzJ1OIAAEBqGQ7vL7/8UnXr1pXFYtHPP/+s2NhYSdKZM2cUFhaW2fUBAIB/yHB4h4eHa9asWZo+fbpcXFzsy2vVqqWoqKhMLQ4AAKSW4fDev3+/qlWrlmp57ty5dfny5UwpCgAA3FmGw7tEiRLatm1bquWrVq1S+fLlM6UoAABwZ+mabX6rIUOGqHv37jp16pSsVqvWrl2rAwcOaOrUqfr000+zokYAAHCLDId369atVbhwYY0cOVKenp7q3bu3goKC9Pnnn6tp06ZZUSMAALhFhsNbkurWrau6detmdi0AACAd7im8bTabvvnmG0VHR0uSypYtq4YNG/JccwAA7oMMh/fu3bvVokULnTx5UmXKlJEk/fHHH/L19dXSpUtVsWLFTC8SAAD8LcNd5Y4dOyo4OFgnTpxQVFSUoqKidPz4cVWuXFkdO3bMihoBAMAt7qnnPX/+fHl7e9uXeXt7KywsTJUrV87U4gAAQGoZ7nlXqVJFe/fuTbV87969hDcAAPdBunrekZGR9u/bt2+vnj17KioqSlWqVJHFYtGWLVs0b948nm0OAMB9YLHZbLa7NUrvLHKLxaLk5OR/XVROtW3bNj3++ONyLt1UFo+Cji4HuO867Yi8eyMgmzqreC3VKUVFRd11JDtdPW+r1ZophQEAgH+PG7MBADDMPT2k5dy5c1q9erWOHj2qxMTEFOuGDh2aKYUBAIDby3B4r1u3Ts2bN9dDDz2k/fv3q1y5cjpy5IhsNpuCgoIIbwAAsliGh8379eunvn37at++fXJ3d9dXX32lY8eO6emnn9YLL7yQFTUCAIBbZDi8f//9d7Vp00aS5OrqqmvXrsnLy0thYWEaO3ZsphcIAABSynB458+fX9euXZMkFS1aVDt37pQkXbhwQVeuXMnc6gAAQCoZDu/Q0FCtWLFCktSuXTu9/vrreu655/TCCy+oSZMmmV4gAABIKcMT1mbOnKmkpCRJUt++feXr66vNmzerf//+6tatW6YXCAAAUspweLu6usrV1dX+um3btmrbtm2mFgUAAO4sXeE9Z86cdO+wU6dO91wMAAC4u3SF94gRI9K1M4vFQngDAJDF0hXehw4dyuo6cIv3/9qjh6/kdnQZwH1XsE6Ao0sAHCb6yhUtjTqVrrY82xwAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADDMPYX34sWL1aBBAz3yyCM6cuSIJCkiIkKrV6/O1OIAAEBqGQ7vadOmqWfPnqpbt66OHz9uf1Rq7ty5NWbMmEwvEAAApJTh8J40aZLmzJmjAQMGyMnJyb68SpUq2rVrV6YWBwAAUstweB85ckQVKlRItdxisSguLi5TigIAAHeW4fCuUKGC1q1bl2r5okWL9Pjjj2dKUQAA4M4y/Kli7733np5//nnt3btXSUlJmjNnjqKjo7Vy5Up9++23WVEjAAC4RYZ73vXr19eWLVt0/vx5VaxYUUuXLpWzs7N++eUX1axZMytqBAAAt8hwz1uSypQpo9mzZ2d2LQAAIB0yHN4HDx5Mc33JkiXvuRgAAHB3GQ7vUqVKyWKxyGaz2ZdZLBb798nJyZlTGQAAuK0Mh/c/P9s7MTFRu3bt0siRIxUeHp5phQEAgNvLcHgHBASkWlaqVCnlz59f/fr1U5MmTTKlMAAAcHuZ9sEkhQsX1u+//55ZuwMAAHeQ4Z53ZGRkitc2m02nTp3SxIkTFRISkmmFAQCA28tweNevXz/Fa4vFokKFCumpp57S+PHjM60wAABwexkOb6vVmhV1AACAdMrQNe/ExERVrlxZ0dHRWVUPAAC4iwyFt4uLi06fPk3vGwAAB8rwbPO+fftqxIgRio2NzYp6AADAXaT7mvePP/6o6tWra+nSpdqxY4d8fX31yCOPyMPDI1U7AACQddId3qGhoTp58qTq16+fasY5AAC4f9Id3jefZT5s2LAsKwYAANxdhq553/oBJAAAwDEydJ93ixYt5Orqmmabfz6BDQAAZK4MhXdISIg8PT2zqhYAAJAOGQrv/v37q3DhwllVCwAASId0X/PmejcAAA+GdIf3zdnmAADAsdI9bM4jUQEAeDBk+PGoAADAsQhvAAAMQ3gDAGAYwhsAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwxDeAAAYhvAGAMAwhDcAAIYhvAEAMAzhDQCAYQhvAAAMQ3gDAGAYwhsAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwxDeAAAYhvAGAMAwhDcAAIYhvAEAMAzhDQCAYQhvAAAMQ3gDAGAYwhsAAMM4O7oA4HaqL/lYBWtUSbHsQtRO/dy0jQpUr6IaX36sv7Zu1y/N2tnXewQWU70N3+i7kKcVe+xEptfk26i+Aju0Vt6gCnLxzqOVxYJkS05O0abI03VUpu/r8no4UAkXLunkqm+1b+QHsiYkSpJK9eysh5o0kGfJQCVdvaYzP/ysfSM+UMJfFzK9Xpir+rr1aa7f82YveVeqpGIdOkqSrImJij91SqdXLNfJxV9kej0WJycVe7Wz8lWrJjdfPyVduqTzP67X0TmzZY2LkyR5B1XSQ61ayatsOeVyc9O1gwd0dPZsXd6xPcW+fCo/rmKvvirPhx9W8vVYnf12rQ5Pm5rpNWd3hDceWAdnfKL9U2fbX1sTE1Os93m0nArXe0pnvv/xvtTjlNtd53/ZonM/bVK5gW+mWu8RUExPzJig39+frBPL18ij2EMKnvSekq5dV/TYyZKk/CHBOjD9E13atUfOXp569N2BejxinDa2fOW+vAeY4dfnWti/f+i//1WecuUVPXSIfVnSlcvyrlRJV/btVfSgQbK4OCtv1aoq2estJV64oHPffZup9eRyd5dnyZI6+vEcXT9wQK6FCqtk7z5y9vLSgbFjJEleFSroanS0js2fr6RLl1SoUSOVGz1GOzu/orijRyVJ3pWCVXr4CB39eLb2jxqpXC6uci1SOFNrzSkIbzywkq7HKv7s+Tuuj/nkc5V9p+d9C+/jS1dKkgpUr3Lb9T4Vyyk5NlYHps6RJMUePa4Ty1crb1AFe5st7V5Lsc2eYWNUc8VCOefxUtKVq1lUOUyTeOEv+/fWuDhZkxJTLLvJlpRkX35mxQoVqFVb+apXz/TwTr52Tfveedv+Ou74cR2d+7FK9npTB3QjvE8sWphim6OzZ6nAU7WVt0qITv0vvAO6d9fJLz7XqS+/tLe7fuhgptaaUxDeMNb+qXNU/L/Pya/J0zq5cm26tmn055Y01+96O1zHl626p3ou7dqrXO7u8m1UX6e++U7uD/mqcGhNHfl06R23cc2fV8mxcUq+HntPxwRuZU2Il8X59v/WXQsXVqW589Lcft877+jKb7vSdSwXHx8lXbl85wYWi5y9vZV0+UYbl3z55VW6jM6uXaOKH02Xa6FCurp3rw5NnayE06fTdUz8jfDGA6vUa51UsvPf17R39hmqE8tX218nXriogzPnq0y/Hjr59Xfp2uf6Bs+nuT6tnv7dXD9yTFs79FDlae/r8Yj3lcvFRYfnf6GDMz65bftcri4q/VZ3HV28PNW1cyCjvCtXVt4qVXR4+vTbrk84d167Xn01zX0knDubrmM558kjv5YtdXr58ju28XvhRdmsVl3YuEGS5ObrK0nyf6mtYqZMVtyJEyr28ssqN3qsdr7SSbLyN5ARD2x4z507VxEREdq0aZOjS4GDHF60JEXwxZ85l6rNwenzVKLjf1X0+Sb6a+v2VOv/6XrM0Uyt8VZuRQqp4ntDdHD6PJ369gd5FPXToyMG6OHXOurAtI9TNs6VS8GTR0uS9g5/P8tqQvaWp3wFhXz9jSxOTpIsOvP1Kp36atntG1uTFXfi+L8+Zi43N5V5d5RiDx3Sic8/u22b/LVqqViHjvp94AAlX7v2vw0tkqTT//eVzq+LlCTtH/2enli6THkqVEh3jx83ODy8Fy9erPHjx2v37t3y8PBQ+fLl1adPH4fVc/jwYQUFBenrr79WjRo17MvffPNN7du3T2vWrHFYbTlN4sXLdw3bpKvXtH/aHJXu3V1b2r1+131m5bB54MutFXvshP6cNEOSdGXfHzcmpY0YmDK8LRYFfzhSXqVKaMPzHRgyxz27tv9P/Tl8uKxJiUo4d06yWu/YNjOGzS0urio76j3ZkhIVPWzYbY+Xt1p1lRowUH8MD9flnTvsyxMv3LijIvbo33/TSZcvK/HSJbkVLqwraVaGf3JoeE+cOFEjRozQtGnT1KhRI3l4eOiHH37QokWLVKtWrUw7TnJysiwWi3Lluvtt7QEBARozZow6duyonTt3yt3dXRs3btS8efO0axdnhg+imI8/VcnO7VX8pefu2jYrh82dcrvL9o9/ZjarTbJYUiwLGj9ceSs/pg0t2ivxYhrXDIG7sCYkpLs3/W+HzS0uLir77rvK5eauvX37yJaYkKqNT5UqKj10mA68P0YX/zFqGn/ypBL++kvu/v72ZU6eXnLx8VE817wzzGEPabl8+bIGDRqkqVOnqmXLlsqTJ4+cnJxUr149zZ799+1BgwYNUoECBeTv76+FC/+ezVinTh1FRETYX69evVqBgYH214GBgRo9erSCg4Pl6empM2fOyGKxaMaMGSpbtqx8fHzUtm1bJSSk/gXs2rWrihcvriFDhig+Pl6vvPKKxo0bp6JFi2r8+PEqXbq08ufPr8aNG+vYsWOSJJvNpt69e6tIkSLy9vbWo48+qm3btmXBTw7/lBwbpz8nzVDgy63v2vZ6zNE0v5KvXb/jti55veVdoYw8SxSXJHmXLyPvCmXk5JFbknQm8icVfDJEJV5pK4/iRVXgyRCV6ddDp7/7+57dx8YMVZEGtbW9xzuSJLdCBeRWqICUjhNL4F/537B5Wl/W2/w/lG7c5106bLjc/f21f8xoOeXOLZd8+eWSL7+9jXelYJUZ/q6OLZivyzt22tfncr/x9yGbTaeWfim/F15Q3mrV5F6suB7u10/XYw7ryt499+MnkK04rOe9YcMGxcXF6bnn7txbioqKUrt27XT69GktX75c7du3V9OmTeXt7Z2uYyxYsEDLly9X0aJF5eTkJElaunSpNmzYoKSkJFWvXl0LFixQp06dUm07e/ZsBQUFaf/+/SpevLheeeUVTZ48WYsWLdLatWvl7++v8PBwtWrVSr/88ovWrl2r9evXKzo6Wj4+Pvrjjz/k6el527pOnjypkydPplq+b9++dL0vpHZ4wWI93K2DPIr5373xPSrydKiCPxxpf/3UmhsPw9jwfEed37hV537apB29h+jhbh1UbmAvJVy4pNPfrte+URPs2wS0aylJqvV1ymuFWfVgGSAzuBYspPz/u4wY/Mn8FOs2htaWJBVq2FBO7u4K6NxFAZ272Ncfnfuxjs2bK0k6vmihcrm76+F+7yiXq4su79yl3wf2T3O4H7dnsdlsNkcceOHCherTp49OnTp12/Vz585VWFiYYmJi7Mu8vb0VGRmpJ554QnXq1FHr1q3VrVs3STd63t26dbO3DwwMVP/+/e3rJclisWjdunWqU6eOJOmNN96Q1WrVlClTblvDlClT1K9fP/35558qWrSoypcvr/Hjx6tRo0aSpKSkJHl6eurPP//U/v371a1bN82bN09Vq1ZNc4g+LCxM4eHhd1w/oWBJPeyS+47rgeyqYJkCji4BcJjoK1fUMWq7oqKiVLly5TTbOmysrkCBAjp37pwS//HUrFv5/u/Wgps8PDx09Wr6H2RRvHjxNPd56/4aNWokLy8veXl5adSoUZKkRx99VD4+PipatKgkKSYmRq1atVLevHmVN29eFSxYULly5dKxY8dUt25d9ejRQz179lThwoX1yiuv6MKF2z/ysmvXroqKikr1tWDBgnS/NwBAzuWwYfMaNWrI3d1dy5YtU8uWLTO8vZeXl65f//v65O168OmZoHbTN998c9c2xYsXV0REhL3n/k9vvPGG3njjDZ09e1atW7fWqFGj9P77qW8D8vPzk5+fX7prAwDgVg7reXt7e2vkyJHq0aOHlixZoqtXryo5OVnr169X586d77p9cHCwfbujR49q8uTJWV5z9+7dNWjQIB04cECSdOHCBX3xxY3rnlu3btXmzZuVmJgoDw8Pubm52a+zAwCQmRw6xbVXr16aMmWKxo0bpyJFisjPz09hYWFq3rz5Xbd966235OPjIz8/P7Vo0UJt2rTJ8np79uypVq1aqUmTJvL29lZQUJD9vu/Lly+rS5cuypcvn4oXLy5vb28NGDAgy2sCAOQ8DpuwhtS2bdumxx9/nAlryLGYsIaczIgJawAA4N4Q3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwxDeAAAYhvAGAMAwhDcAAIYhvAEAMAzhDQCAYQhvAAAMQ3gDAGAYwhsAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwxDeAAAYhvAGAMAwhDcAAIYhvAEAMAzhDQCAYQhvAAAMQ3gDAGAYwhsAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwxDeAAAYhvAGAMAwhDcAAIYhvAEAMAzhDQCAYQhvAAAMQ3gDAGAYwhsAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbAADDEN4AABiG8AYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwzg7ugD8LTY2VpJ0NCnewZUAjnH+yhVHlwA4TMz165L+zoK0EN4PkJiYGEnSBxePO7YQwFHOOboAwPFiYmL05JNPptnGYrPZbPepHtzFuXPntGbNGgUGBip37tyOLidH2rdvn9q2basFCxaoXLlyji4HuK/4/Xes2NhYxcTEqGHDhipYsGCabel5P0AKFiyoNm3aOLoMSCpXrpwqV67s6DIAh+D333Hu1uO+iQlrAAAYhvAGAMAwhDcAAIYhvAEAMAzhDdzCz89Pw4YNk5+fn6NLAe47fv/Nwa1iAAAYhp43AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbyARWqzXVMm7kQE6SlJRk/z4hIcGBleQMhDfwLyUlJSlXrht/SsePH9eRI0ckSRaLhQBHjpCcnCxnZ2dZrVa1bt1a3333na7/77OpkTX4VDHgX7BarfZ/Wo0bN9bly5cVFxengIAALVmyRE5OTrJarfZwB7Kjm7/nwcHBCgwMVPXq1eXh4eHosrI1HtICZIImTZrI19dXQ4YM0YkTJ9SjRw85Oztr8+bNji4NuC+GDh2qAwcOaOHChZKklStXytnZWZ6enqpVq5aDq8t+6HkD/9KJEyf0119/aeLEiQoICFBAQIA2bdqkSpUqadCgQRo5cqSjSwSynLe3t65cuaLo6GiFh4dr165dKlCggNzd3fXRRx+pZMmSji4xW2EsD8igbt26qWPHjvbXLi4uypUrl/bs2SPpxvU/FxcXNWvWTJcvX3ZUmUCWSU5OTrWsUaNGSk5OVu/evWW1WvXbb78pIiKCy0ZZhJ43kEGdOnVS3bp1lS9fPn3wwQcqVKiQAgMDNX78eFWpUkWFCxeWdON6eGJioqxWqywWiywWi4MrB+6NzWZL8ft78xr3O++8Yz95HTp0qL744gtdu3ZNBQsWlMVi0U8//aRjx47J3d3dgdVnT1zzBtJwp17D9u3bVbNmTXXq1EmTJ0+WJFWrVk3u7u4qW7as8ubNq5kzZ+rHH39UhQoV7nfZQJb4+uuv1bhxY1mtVj3xxBN66KGH1LRpU82aNUtWq1VLly5VQECAYmJiFBERoZkzZ+rbb79V5cqVHV16tsNYBpCGm8G9atUq7dy5U9KNIcPg4GCtX79ec+fOVdeuXSVJmzZtUuPGjeXh4aH4+Hj99NNPBDeyjWXLlmnMmDGSpHnz5qlEiRJauXKlunbtqipVqshisah48eKSpIsXLyoxMVHr168nuLMIw+bAXbz77rsaOnSoChQooODgYIWEhKh+/fqqU6eO9uzZo8cee0yenp764IMP9Pbbb0u6c48dMFW+fPm0b98+xcbGKjY2Vq6urpKkNm3a6LffflNUVJTOnz+vn3/+Wc2bN1eFChXk4uLi4KqzL8IbuItKlSqpfv368vf3l9VqVXJystq0aaPAwECFhobqrbfeUnh4uHLnzm2fWc71bZjs1mvcN09Eg4KCFBgYqDNnzsjPz0/x8fFq27at9u3bp+3bt8vJyUlz585VZGSk6tWrpzx58jj4XWRvXPMG0mHZsmVasmSJihQpov79+8tqtSo6OloffPCB8uXLp08++URubm46evSoChYs6OhygUyxa9cueXt7KzAwUNKNGeUtW7ZUu3bt9NRTT2nTpk3as2ePypUrpylTpig8PFyRkZGqWLGiYwvPAQhvIA239kC+/PJLzZ8/XwEBAerevbvKli0r6cZznH/88Uc9/PDDKlGihCPLBTLNZ599pp49e8rHx0clSpSQp6enzp49q/r16ys8PFyxsbF69tln5ebmpmvXrik+Pl5Tp05VcHCwo0vPEQhv4C4SExPt1+5WrVqlGTNmqGTJknr11VeZkIZs7cyZM4qNjdXmzZv122+/KTo6WqtXr9aUKVPUvn17JSYm6vDhw3J2dpaPj4/y5cvn6JJzDMIbSENycrKcnJwkSZGRkapbt66WLVumRYsWKW/evOrXr59Kly7t4CqB+yMhIUEREREaNWqUxo8frzZt2ji6pByLCWvA/9wa1DfdfN2qVStdvXpVdevWVYsWLRQfH69Vq1bJx8fHEaUC98WtfxPffvutatasqVdffVUWi0UdOnSQu7u7nn/+eQdXmTPR8wZ042M9nZ2dZbPZ9OuvvyogIEA+Pj5yc3NTr169tG7dOkVFRaW49eXq1avy8vJyYNVA5rndyetNrVq10vXr17V8+XJZLBZdu3ZNCxYsUGhoKCNPDkJ4I8e7OSnNarWqWrVqunDhggoWLKimTZuqd+/e+vHHH1W7dm25ubkpKSlJTk5O3AqGbOVeTl7hWDxFAjnarbPJ33vvPT366KPas2ePnnvuOW3btk3h4eEKCQmRm5ubEhIS5OzsTHAjW7HZbPbPpK9atapeeuklNWvWTOPHj1dcXJyeeeYZbd26VS4uLkpKSnJ0ufgfwhs5VnJysiwWi2w2m/7zn/9o165d6tKli1xdXdW7d281atRI0dHRGj16tC5cuGB/ohSQXdzLySseDIQ3ciSr1SonJyclJiZq//79Klu2rBYvXqzdu3dLujFRrVOnTmratKl+/fVXTZgwQVxhQnbCyavZOI1CjnPrxJyKFSuqRo0amjNnjpydndW3b1+VK1dOTz75pH1GrYuLi+rUqcNwObKNW09eY2JiVLZsWU2aNEkNGjRQtWrV7CevuXLl0sKFCzVhwgSFh4fzN/AAIbyR4zg5Oclms+n//u//FBoaqo8++kiSNG7cOCUmJqpx48b65ptvVKNGDVksFrVt29bBFQOZh5PX7IHwRo5x6yd9TZs2TT179tSjjz6qU6dOydfXV5I0ceJEOTk5qWbNmtq4caOqVq3qyJKBTMfJa/ZAeCPHuPUjOl9//XVdvHhRERER2rhxoxo3biw3NzdJ0gcffCBXV1flzZvXQZUCmY+T1+yF8EaO0qFDByUlJWnBggUaNGiQ/vrrLw0cOFBOTk5q2LChPcBHjx7t4EqBzMXJa/bCQ1qQYyQmJmrVqlUKCwtTzZo1NWXKFElS3759tXbtWg0ZMkTNmjVjVi2yrVtPXiWpT58++vrrrzVmzJgUJ6948HGrGLItq9Vq/z4pKUkuLi5q1KiRRo8erfXr1+u1116TdONaX40aNTRu3DglJCQ4qlwgSyUmJqp58+bavXu3evToIUkaP368nnnmGQ0ePFjLly/n998g9LyRrdlsNg0cOFDBwcFq0aKFXFxcFBcXpx9//FE9e/bUiy++qHfffVfSjY8/LFy4sIMrBjLHrde4bz7+ND4+XuvWrVO/fv1Uq1YtTZs2TZLUrVs3bd++Xd9//z3P6zcEPW9kO7eejyYlJWnv3r1auHChvvnmGyUkJMjd3V1Vq1ZVqVKlNGrUKPXt21eSVKhQIUeVDGS6XLlyyWazacCAAVq6dKkSExPl5uamOnXqaPz48fr+++81ePBgSVJERIRWrFhBcBuECWvIVuLi4uTu7i5Jio2NVe7cufX555/r9ddf14wZM5QrVy41aNBAPj4+CgkJUYsWLVSvXj1J4j5WZAu3PvL05snr3r175e7urv/85z+pTl7j4uI0btw4Tl4Nw7A5jHfkyBEtWrRI/fv3lyQlJCSoa9euunr1qqpXr67evXsrISFBr732ms6ePauHH35YPj4+mjlzpjZu3KhixYo5+B0AmeN2J69xcXF6/fXXdfr0aXXr1k0NGjSQm5ubwsPD5e/vr3r16qlEiRIOrhwZRXjDWDd7GF988YWGDx+uF154QWFhYXrmmWeUnJys+vXra/jw4erQoYM++OAD2Ww2ffjhh9qxY4dOnDihCRMmqFKlSo5+G8C/wslrzkR4w0i3Dg0ePHhQGzZs0Pz58+Xv768CBQro/ffflyTt3LlTzz77rJo1a6b333/ffivMzV4JYCpOXnM2whvGuTW4+/TpY5+I89hjj2nSpEm6du2a9u7da28fFRWlli1bKjQ0VGPGjFGBAgUcVTqQKTh5BeENYzVv3lyXLl3S+PHj9dBDD8nX11cLFixQWFiY/vvf/2rEiBH2tps2bVLnzp313XffqUiRIg6sGvh3OHmFRHjDUO+8844iIyO1devWFMuvXLmir776StOnT1fdunU1fPhw+7r4+HieIIVsg5PXnI3whnHi4+PVrl07tW/fXk2aNFFiYqJcXFzs6xMSEvT5559r4cKFKlu2rD788ENJKXssgMk4eQUPaYFx4uLi9Ntvv+nq1auSZP9s4ptcXV116dIlPffcc/rzzz919uxZSdzHjewhPj5ehw4d0rBhwyTdeOzpTXny5FGrVq3UtWtXbdmyRW+++aZ9Hc/sz14IbxjHyclJuXPn1s6dOyXdeJKU1Wq1P8v88uXL2rdvn5544gl9+umnPHwC2Qonr5AIbxjIy8tL/fr104QJE7Ro0SJJNwL85nOc58+fr127dqlEiRLy9vZ2ZKlApuPkFRKPR4WhWrRooT179qh79+46ceKEXnjhBSUlJWnx4sV6//33tW7dOuXLl8/RZQKZ7ubJa8eOHVWxYkW99NJLKT6rm5PXnIHwhpHc3d01YMAA+fn5aciQIYqIiFCBAgXk5uamyMhIBQUFObpEIMtw8gpmm8N4p06d0tmzZ5UnTx7ly5dPPj4+ji4JyHLXrl3T3LlzNWTIEOXPn99+8jpp0iSenJYDEN4AYDBOXnMmwhsAAMMw2xwAAMMQ3gAAGIbwBgDAMIQ3AACGIbwBADAM4Q0AgGEIbwAADEN4AwBgGMIbQIa1bdtWHTp0sL8ODAzUrFmz7msNgwcPVp06de64PiwsTDVr1kz3/jp06KC2bdv+q5oc8XNAzkR4A9lInTp1ZLFYZLFY5OXlpZCQEK1ZsybLj7t161a1adMmXW1r1qypsLCwrC0IyOYIbyCbefPNN3Xy5Elt375dlStXVrNmzbR///5U7Ww2mxITEzPlmIUKFVLu3LkzZV8A7o7wBrIZT09P+fr66pFHHtGUKVPk5OSk7777TpJksVg0a9Ys1a1bV7lz59bKlSslSZMmTVLJkiXl4eGhKlWq6Icffkixz8mTJ6tIkSLy8fFRnz599M+PRPjncPGBAwfUrFkzeXt7y8fHR/Xr19eFCxfUoUMH/fLLLwoPD5fFYlFgYKB9m88++0zly5dX7ty59eijj2rJkiUpjrF48WIFBATI09NT7du3V1xcXIZ+LrNnz1alSpXk6empgIAADRkyRElJSSna2Gw29enTRz4+PipSpIgmTZqUYv3BgwfVtGlTeXl56aGHHlKPHj10/fr1DNUBZAbCG8jGnJ2d5eLikqKHHRYWptdee0179+7Vk08+qTlz5mjixImaNm2adu/erfbt26tx48aKiYmRJK1fv169e/dWeHi4Nm/erNjYWC1fvvyOx4yPj9fTTz8tq9WqdevWafPmzXruueeUnJysiRMnKiQkRH369NHJkye1detWSVJkZKR69uyp8PBw7dmzRwMHDlT79u21adMmSTdOBl566SW9+uqr2rZtmx555BFNnz49Qz8Lq9WqcePGaffu3YqIiNCsWbM0Y8aMFG2WL1+u2NhYbd68WSNGjFDfvn3tJzIJCQlq2LChHnnkEUVFRen//u//tHXrVvXp0ydDdQCZwgYg26hdu7Zt0KBBNpvNZktISLC99957tly5ctm2b99us9lsNkm2sLCwFNuUKFHCtmLFihTLGjRoYBsxYoTNZrPZWrZsaWvVqpV9XWJios3f39/28ssv25cFBATYZs6cabPZbLY5c+bYChUqZLt27dpta3zyySdtw4YNS7EsNDTUNnny5BTLOnfubHvllVdsNpvN9vbbb9uqVq2aYn3VqlVttWvXvsNPwmYbNmyY7cknn7zj+vfee88WGhpqf/3yyy/b/P39bYmJifZlbdq0sT3//PM2m81mmzdvnu3xxx9PsY9ffvnF5urqaktKSrLZbCl/DkBWcnb0yQOAzDV27Fh9+OGHio+Pl7e3tz766CNVqlTJvj44ONj+/dWrV3Xo0CG1atVKFovFvjw+Pl5FixaVJEVHR6t9+/b2dc7OzqpcufIdj797926FhITIw8Mj3TX/9ttv2rhxo/r3729flpCQYJ8tHh0drZCQkBTbhISEaNeuXek+xoYNGxQWFqY9e/bo0qVLSkpKUrFixVK0qVy5spyd//63GBISopkzZ9pr3Llzp7y8vOzrbTabEhISdPz4cRUvXjzdtQD/FuENZDOdO3fWW2+9JS8vL/n6+qZaf2uoXrt2TZK0aNEiVahQIUW7PHnySLoRULcG+93Y/nE9PD2uXr2qcePGqWHDhimW35wEl9Ea/unKlSt65pln1LJlSw0fPlz58+fXokWLNHfu3BTt0jrG1atX9dRTT912uN7Pz++eawPuBeENZDP58uVTqVKl0tW2cOHC8vX11ZEjR9SsWbPbtilTpoy2bNlif52cnKzt27erXr16t21fsWJFLVy4UNevX79t79vFxUXJyckplgUFBengwYN3rLtMmTL66aefUizbunWr3Nzc0nx/N0VHR+vixYsaM2aM8ubNK0k6evRoqnbbtm1TcnKynJyc7McoU6aMvcbly5eraNGicnd3T9dxgazChDUgB7NYLBo4cKCGDBmijz/+WAcOHNCvv/6q0aNHKzIyUpLUvXt3LVmyRDNmzFB0dLR69eqlixcv3nGfL730kry8vNSqVStFRUXpjz/+0PTp03Xu3DlJUkBAgDZt2qTjx4/rwoULkqSBAwdq6tSpmjBhgv744w/t3LlTU6ZM0eeffy5J6tKli7Zu3aqRI0fqjz/+0MiRI7V79+50v8/ixYvLxcVF06ZN08GDBxUREaGvvvoqVbuLFy+qV69eio6O1qxZs/T555/r9ddflyS1adNGrq6uatWqlbZu3ar9+/drxYoV6tu3b7rrADIL4Q3kcD179tTYsWM1duxYlStXTk2bNtWWLVvk7+8vSQoNDdW4ceM0ePBgValSRU5OTmratOkd9+fm5qY1a9bIarXqqaeeUpUqVfTll1/aryX37dtX58+fV8mSJe3X35999ll9+umnmj9/vipWrKj69etr5cqVCggIkCSVKlVKCxYs0PTp0xUcHKy9e/eqS5cu6X6PhQsX1owZMzRt2jRVrFhRa9euTXF9/aZnn31Wzs7OCgkJ0cCBAzV27FiFhoZKunEZ4YcffpCrq6saNGigoKAgDR48mCFzOITFdi8XqAAAgMPQ8wYAwDCENwAAhiG8AQAwDOENAIBhCG8AAAxDeAMAYBjCGwAAwxDeAAAYhvAGAMAwhDcAAIYhvAEAMAzhDQCAYf4fGUakunjmL1UAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall=0.554 \n",
      "Precision=0.693\n",
      "F1=0.792\n",
      "Average precision-recall score: 0.679\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = (5,5)\n",
    "\n",
    "# Making a list of all classifiers\n",
    "classifier_model = [LogisticRegression(max_iter=1000), KNeighborsClassifier(), GaussianNB(), SVC(), DecisionTreeClassifier(), RandomForestClassifier(), SGDClassifier(), AdaBoostClassifier()]\n",
    "\n",
    "# Creating empty list to store the performance details\n",
    "classifier_model_list= []\n",
    "classifier_accuracy_test = []\n",
    "classifier_accuracy_train = []\n",
    "f1score = []\n",
    "precisionscore = []\n",
    "recallscore = []\n",
    "avg_pre_rec_score = []\n",
    "cv_score = []\n",
    "\n",
    "for classifier_list in classifier_model:\n",
    "    classifier = classifier_list\n",
    " \n",
    "    # Fitting the training set into classification model\n",
    "    classifier.fit(X_train,y_train)\n",
    "    \n",
    "    # Predicting the output on test dataset\n",
    "    y_pred_test = classifier.predict(X_test)    \n",
    "    score_test = accuracy_score(y_test, y_pred_test)\n",
    "    \n",
    "    # Predicting the output on training datset\n",
    "    y_pred_train = classifier.predict(X_train) \n",
    "    score_train = accuracy_score(y_train, y_pred_train)\n",
    "    \n",
    "    # Cross Validation Score on training test\n",
    "    scores = cross_val_score(classifier, X_train,y_train, cv=10)\n",
    "    cv_score.append(scores.mean())\n",
    "    \n",
    "    #Keeping the model and accuracy score into a list\n",
    "    classifier_model_list.append(classifier_list.__class__.__name__)\n",
    "    classifier_accuracy_test.append(round(score_test,4))\n",
    "    classifier_accuracy_train.append(round(score_train,4))\n",
    "    \n",
    "    #Precision, Recall and F1 score\n",
    "    f1score.append(f1_score(y_test, y_pred_test, average='weighted'))\n",
    "    precisionscore.append(precision_score(y_test, y_pred_test))\n",
    "    recallscore.append(recall_score(y_test, y_pred_test))\n",
    "    \n",
    "    #Calculating Average Precision Recall Score\n",
    "    try:\n",
    "        y_pred_score = classifier.decision_function(X_test)\n",
    "    except:\n",
    "        y_pred_score = classifier.predict_proba(X_test)[:,1]\n",
    "    \n",
    "    from sklearn.metrics import average_precision_score\n",
    "    average_precision = average_precision_score(y_test, y_pred_score)\n",
    "    avg_pre_rec_score.append(average_precision)\n",
    "    \n",
    "    \n",
    "    #Confusion Matrix\n",
    "    plot_confusion_matrix(classifier_list.__class__.__name__, y_test, y_pred_test)\n",
    "    plot_prec_rec_curve(classifier_list.__class__.__name__, y_test, y_pred_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3d7d681-8889-4cc8-9bc7-17c42b6e1e6e",
   "metadata": {},
   "source": [
    "### Classification Model Performance Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "09f48cb9-f925-4482-96d8-d55f67b62451",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "*------------------------------    CLASSIFICATION MODEL PERFORMANCE EVALUATION      ---------------------*\n",
      "\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>Model</th>\n",
       "      <th>Cross Val Score</th>\n",
       "      <th>Test Accuracy</th>\n",
       "      <th>Average_Accuracy</th>\n",
       "      <th>Precision</th>\n",
       "      <th>Recall</th>\n",
       "      <th>Avg Precision Recall</th>\n",
       "      <th>F1 Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AdaBoostClassifier</td>\n",
       "      <td>0.808885</td>\n",
       "      <td>0.7996</td>\n",
       "      <td>0.804242</td>\n",
       "      <td>0.693252</td>\n",
       "      <td>0.553922</td>\n",
       "      <td>0.679373</td>\n",
       "      <td>0.792329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LogisticRegression</td>\n",
       "      <td>0.807994</td>\n",
       "      <td>0.7982</td>\n",
       "      <td>0.803097</td>\n",
       "      <td>0.689024</td>\n",
       "      <td>0.553922</td>\n",
       "      <td>0.647582</td>\n",
       "      <td>0.791068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SVC</td>\n",
       "      <td>0.789680</td>\n",
       "      <td>0.7761</td>\n",
       "      <td>0.782890</td>\n",
       "      <td>0.680934</td>\n",
       "      <td>0.428922</td>\n",
       "      <td>0.647102</td>\n",
       "      <td>0.758567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SGDClassifier</td>\n",
       "      <td>0.785604</td>\n",
       "      <td>0.7662</td>\n",
       "      <td>0.775902</td>\n",
       "      <td>0.748428</td>\n",
       "      <td>0.291667</td>\n",
       "      <td>0.625513</td>\n",
       "      <td>0.727781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KNeighborsClassifier</td>\n",
       "      <td>0.764976</td>\n",
       "      <td>0.7726</td>\n",
       "      <td>0.768788</td>\n",
       "      <td>0.622222</td>\n",
       "      <td>0.549020</td>\n",
       "      <td>0.575438</td>\n",
       "      <td>0.768126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RandomForestClassifier</td>\n",
       "      <td>0.760886</td>\n",
       "      <td>0.7541</td>\n",
       "      <td>0.757493</td>\n",
       "      <td>0.589080</td>\n",
       "      <td>0.502451</td>\n",
       "      <td>0.598013</td>\n",
       "      <td>0.747913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DecisionTreeClassifier</td>\n",
       "      <td>0.739016</td>\n",
       "      <td>0.7413</td>\n",
       "      <td>0.740158</td>\n",
       "      <td>0.561111</td>\n",
       "      <td>0.495098</td>\n",
       "      <td>0.430856</td>\n",
       "      <td>0.736244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GaussianNB</td>\n",
       "      <td>0.700626</td>\n",
       "      <td>0.7029</td>\n",
       "      <td>0.701763</td>\n",
       "      <td>0.493132</td>\n",
       "      <td>0.879902</td>\n",
       "      <td>0.609515</td>\n",
       "      <td>0.716429</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Model  Cross Val Score  Test Accuracy  Average_Accuracy  \\\n",
       "7      AdaBoostClassifier         0.808885         0.7996          0.804242   \n",
       "0      LogisticRegression         0.807994         0.7982          0.803097   \n",
       "3                     SVC         0.789680         0.7761          0.782890   \n",
       "6           SGDClassifier         0.785604         0.7662          0.775902   \n",
       "1    KNeighborsClassifier         0.764976         0.7726          0.768788   \n",
       "5  RandomForestClassifier         0.760886         0.7541          0.757493   \n",
       "4  DecisionTreeClassifier         0.739016         0.7413          0.740158   \n",
       "2              GaussianNB         0.700626         0.7029          0.701763   \n",
       "\n",
       "   Precision    Recall  Avg Precision Recall  F1 Score  \n",
       "7   0.693252  0.553922              0.679373  0.792329  \n",
       "0   0.689024  0.553922              0.647582  0.791068  \n",
       "3   0.680934  0.428922              0.647102  0.758567  \n",
       "6   0.748428  0.291667              0.625513  0.727781  \n",
       "1   0.622222  0.549020              0.575438  0.768126  \n",
       "5   0.589080  0.502451              0.598013  0.747913  \n",
       "4   0.561111  0.495098              0.430856  0.736244  \n",
       "2   0.493132  0.879902              0.609515  0.716429  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Creating pandas dataframe with Model and corresponding accuracy\n",
    "#accuracy_df = pd.DataFrame({'Model':classifier_model_list , 'Test Accuracy':classifier_accuracy_test, 'Train Accuracy' :classifier_accuracy_test , 'Precision':precisionscore, 'Recall':recallscore ,'F1 Score':f1score},index=None)\n",
    "accuracy_df = pd.DataFrame({'Model':classifier_model_list , 'Cross Val Score':cv_score, 'Test Accuracy' :classifier_accuracy_test , 'Precision':precisionscore, 'Recall':recallscore ,'Avg Precision Recall':avg_pre_rec_score ,'F1 Score':f1score})\n",
    "\n",
    "# Calculating Average Accuracy = (Test + Train)/2\n",
    "accuracy_df['Average_Accuracy'] =  (accuracy_df['Cross Val Score'] + accuracy_df['Test Accuracy'] )/ 2\n",
    "\n",
    "#Arranging the Columns\n",
    "print(\"\\n*------------------------------    CLASSIFICATION MODEL PERFORMANCE EVALUATION      ---------------------*\\n\")\n",
    "accuracy_df = accuracy_df[['Model','Cross Val Score', 'Test Accuracy', 'Average_Accuracy','Precision', 'Recall','Avg Precision Recall','F1 Score']]  # This will arrange the columns in the order we want\n",
    "\n",
    "#Sorting the Columns based on Average Accuracy\n",
    "accuracy_df.sort_values('Average_Accuracy', axis=0, ascending=False, inplace=True) # Sorting the data with highest accuracy in the top\n",
    "accuracy_df\n",
    "#accuracy_df.transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a85a8342-5265-453f-b398-a71c5644df98",
   "metadata": {},
   "source": [
    "##### Logistic Regression and Adaboost model looks promising (highest Avg Precision Recall and F1 score). Let's try to improve the model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cebe4296-860f-41e4-a8b0-b4d76716a1ea",
   "metadata": {},
   "source": [
    "### Improving our Model: Model Tuning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "119f8980-1b59-452a-920f-261d37ae16e1",
   "metadata": {},
   "source": [
    "#### Grid Search for Logistic Regression Classifier and running with optimized hyperparameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bd7922f5-749d-4ce8-8882-6871b7d64558",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import make_scorer\n",
    "from sklearn.metrics import fbeta_score, accuracy_score\n",
    "from sklearn.linear_model  import LogisticRegression # Logistic Regression Classifier\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "284c9488-e610-4ed9-8785-97fd5d8da0d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final accuracy score on the testing data: 0.7982\n",
      "Final F-score on the testing data: 0.7911\n",
      "LogisticRegression(C=1, max_iter=10000, solver='liblinear')\n"
     ]
    }
   ],
   "source": [
    "# Logistic Regression Classifier\n",
    "clf_log = LogisticRegression()\n",
    "\n",
    "# Hyperparameters\n",
    "parameters_log = {'solver': ['newton-cg', 'liblinear', 'sag', 'saga', 'lbfgs'],\n",
    "              'C': [0.001,0.01,0.1,1,10,100,1000],\n",
    "              'max_iter': [10000]\n",
    "             }\n",
    "\n",
    "# Make an fbeta_score scoring object\n",
    "#scorer = make_scorer(fbeta_score, beta=0.5)\n",
    "\n",
    "# Perform grid search on the classifier using 'scorer' as the scoring method\n",
    "grid_obj_log = GridSearchCV(estimator=clf_log, param_grid=parameters_log, scoring=f1_weighted)\n",
    "\n",
    "# Fit the grid search object to the training data and find the optimal parameters\n",
    "grid_fit_log = grid_obj_log.fit(X_train, y_train)\n",
    "\n",
    "# Get the estimator\n",
    "best_clf_log = grid_fit_log.best_estimator_\n",
    "\n",
    "# View best hyperparameters\n",
    "#print(grid_fit.best_params_)\n",
    "\n",
    "# Make predictions\n",
    "y_pred_log = best_clf_log.predict(X_test)\n",
    "\n",
    "# Report \n",
    "print (\"Final accuracy score on the testing data: {:.4f}\".format(accuracy_score(y_test, y_pred_log)))\n",
    "print (\"Final F-score on the testing data: {:.4f}\".format(f1_score(y_test, y_pred_log, average='weighted')))\n",
    "print (best_clf_log)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13a45b53-5f8a-40ea-966a-c8eda847d149",
   "metadata": {},
   "source": [
    "#### Grid Search for Adaboost Classifier and running with optimized hyperparameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "0c29a9fd-90f3-4cc4-a3b9-b2e667dbfc13",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final accuracy score on the testing data: 0.7989\n",
      "Final F1-score on the testing data: 0.7917\n",
      "AdaBoostClassifier(n_estimators=100)\n"
     ]
    }
   ],
   "source": [
    "# Adaboost classifier\n",
    "clf_ada = AdaBoostClassifier()\n",
    "# Hyperparameters\n",
    "parameters_ada = {'n_estimators': [10, 50, 100, 500], \n",
    "              'learning_rate': [0.0001, 0.001, 0.01, 0.1, 1.0]\n",
    "             }\n",
    "\n",
    "# Make an fbeta_score scoring object\n",
    "#scorer = make_scorer(fbeta_score, beta=0.5)\n",
    "\n",
    "# Perform grid search on the classifier using 'scorer' as the scoring method\n",
    "grid_obj_ada = GridSearchCV(estimator=clf_ada, param_grid=parameters_ada, scoring=f1_weighted)\n",
    "\n",
    "# Fit the grid search object to the training data and find the optimal parameters\n",
    "grid_fit_ada = grid_obj_ada.fit(X_train, y_train)\n",
    "\n",
    "# Get the estimator\n",
    "best_clf_ada = grid_fit_ada.best_estimator_\n",
    "\n",
    "# Make predictions using the unoptimized and model\n",
    "y_pred_ada = best_clf_ada.predict(X_test)\n",
    "\n",
    "# Report\n",
    "print (\"Final accuracy score on the testing data: {:.4f}\".format(accuracy_score(y_test, y_pred_ada)))\n",
    "print (\"Final F1-score on the testing data: {:.4f}\".format(f1_score(y_test, y_pred_ada, average='weighted')))\n",
    "print (best_clf_ada)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9995c0b0-1ea1-40e7-b32d-cd1e9bcfd175",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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