{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Breast Cancer Prediction and Detection\n",
    "### via Machine Learning and Deep Learning  \n",
    "\n",
    "### David Kinney - DSC680 - Spring 2021 - Professor Catherine Williams\n",
    "**********************************************************************"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import packages\n",
    "import pandas as pd\n",
    "from pycaret.classification import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Breast Cancer Prediction - Machine Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(569, 33)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the Breast Cancer Wisconsin (Diagnostic) dataset\n",
    "df = pd.read_csv('./data/data.csv')\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>569.0</td>\n",
       "      <td>3.037183e+07</td>\n",
       "      <td>1.250206e+08</td>\n",
       "      <td>8670.000000</td>\n",
       "      <td>869218.000000</td>\n",
       "      <td>906024.000000</td>\n",
       "      <td>8.813129e+06</td>\n",
       "      <td>9.113205e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>radius_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.412729e+01</td>\n",
       "      <td>3.524049e+00</td>\n",
       "      <td>6.981000</td>\n",
       "      <td>11.700000</td>\n",
       "      <td>13.370000</td>\n",
       "      <td>1.578000e+01</td>\n",
       "      <td>2.811000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>texture_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.928965e+01</td>\n",
       "      <td>4.301036e+00</td>\n",
       "      <td>9.710000</td>\n",
       "      <td>16.170000</td>\n",
       "      <td>18.840000</td>\n",
       "      <td>2.180000e+01</td>\n",
       "      <td>3.928000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>perimeter_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>9.196903e+01</td>\n",
       "      <td>2.429898e+01</td>\n",
       "      <td>43.790000</td>\n",
       "      <td>75.170000</td>\n",
       "      <td>86.240000</td>\n",
       "      <td>1.041000e+02</td>\n",
       "      <td>1.885000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>area_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>6.548891e+02</td>\n",
       "      <td>3.519141e+02</td>\n",
       "      <td>143.500000</td>\n",
       "      <td>420.300000</td>\n",
       "      <td>551.100000</td>\n",
       "      <td>7.827000e+02</td>\n",
       "      <td>2.501000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smoothness_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>9.636028e-02</td>\n",
       "      <td>1.406413e-02</td>\n",
       "      <td>0.052630</td>\n",
       "      <td>0.086370</td>\n",
       "      <td>0.095870</td>\n",
       "      <td>1.053000e-01</td>\n",
       "      <td>1.634000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>compactness_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.043410e-01</td>\n",
       "      <td>5.281276e-02</td>\n",
       "      <td>0.019380</td>\n",
       "      <td>0.064920</td>\n",
       "      <td>0.092630</td>\n",
       "      <td>1.304000e-01</td>\n",
       "      <td>3.454000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>concavity_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>8.879932e-02</td>\n",
       "      <td>7.971981e-02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.029560</td>\n",
       "      <td>0.061540</td>\n",
       "      <td>1.307000e-01</td>\n",
       "      <td>4.268000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>concave points_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>4.891915e-02</td>\n",
       "      <td>3.880284e-02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020310</td>\n",
       "      <td>0.033500</td>\n",
       "      <td>7.400000e-02</td>\n",
       "      <td>2.012000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>symmetry_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.811619e-01</td>\n",
       "      <td>2.741428e-02</td>\n",
       "      <td>0.106000</td>\n",
       "      <td>0.161900</td>\n",
       "      <td>0.179200</td>\n",
       "      <td>1.957000e-01</td>\n",
       "      <td>3.040000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fractal_dimension_mean</th>\n",
       "      <td>569.0</td>\n",
       "      <td>6.279761e-02</td>\n",
       "      <td>7.060363e-03</td>\n",
       "      <td>0.049960</td>\n",
       "      <td>0.057700</td>\n",
       "      <td>0.061540</td>\n",
       "      <td>6.612000e-02</td>\n",
       "      <td>9.744000e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>radius_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>4.051721e-01</td>\n",
       "      <td>2.773127e-01</td>\n",
       "      <td>0.111500</td>\n",
       "      <td>0.232400</td>\n",
       "      <td>0.324200</td>\n",
       "      <td>4.789000e-01</td>\n",
       "      <td>2.873000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>texture_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.216853e+00</td>\n",
       "      <td>5.516484e-01</td>\n",
       "      <td>0.360200</td>\n",
       "      <td>0.833900</td>\n",
       "      <td>1.108000</td>\n",
       "      <td>1.474000e+00</td>\n",
       "      <td>4.885000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>perimeter_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>2.866059e+00</td>\n",
       "      <td>2.021855e+00</td>\n",
       "      <td>0.757000</td>\n",
       "      <td>1.606000</td>\n",
       "      <td>2.287000</td>\n",
       "      <td>3.357000e+00</td>\n",
       "      <td>2.198000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>area_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>4.033708e+01</td>\n",
       "      <td>4.549101e+01</td>\n",
       "      <td>6.802000</td>\n",
       "      <td>17.850000</td>\n",
       "      <td>24.530000</td>\n",
       "      <td>4.519000e+01</td>\n",
       "      <td>5.422000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smoothness_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>7.040979e-03</td>\n",
       "      <td>3.002518e-03</td>\n",
       "      <td>0.001713</td>\n",
       "      <td>0.005169</td>\n",
       "      <td>0.006380</td>\n",
       "      <td>8.146000e-03</td>\n",
       "      <td>3.113000e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>compactness_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>2.547814e-02</td>\n",
       "      <td>1.790818e-02</td>\n",
       "      <td>0.002252</td>\n",
       "      <td>0.013080</td>\n",
       "      <td>0.020450</td>\n",
       "      <td>3.245000e-02</td>\n",
       "      <td>1.354000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>concavity_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>3.189372e-02</td>\n",
       "      <td>3.018606e-02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015090</td>\n",
       "      <td>0.025890</td>\n",
       "      <td>4.205000e-02</td>\n",
       "      <td>3.960000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>concave points_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.179614e-02</td>\n",
       "      <td>6.170285e-03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007638</td>\n",
       "      <td>0.010930</td>\n",
       "      <td>1.471000e-02</td>\n",
       "      <td>5.279000e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>symmetry_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>2.054230e-02</td>\n",
       "      <td>8.266372e-03</td>\n",
       "      <td>0.007882</td>\n",
       "      <td>0.015160</td>\n",
       "      <td>0.018730</td>\n",
       "      <td>2.348000e-02</td>\n",
       "      <td>7.895000e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fractal_dimension_se</th>\n",
       "      <td>569.0</td>\n",
       "      <td>3.794904e-03</td>\n",
       "      <td>2.646071e-03</td>\n",
       "      <td>0.000895</td>\n",
       "      <td>0.002248</td>\n",
       "      <td>0.003187</td>\n",
       "      <td>4.558000e-03</td>\n",
       "      <td>2.984000e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>radius_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.626919e+01</td>\n",
       "      <td>4.833242e+00</td>\n",
       "      <td>7.930000</td>\n",
       "      <td>13.010000</td>\n",
       "      <td>14.970000</td>\n",
       "      <td>1.879000e+01</td>\n",
       "      <td>3.604000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>texture_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>2.567722e+01</td>\n",
       "      <td>6.146258e+00</td>\n",
       "      <td>12.020000</td>\n",
       "      <td>21.080000</td>\n",
       "      <td>25.410000</td>\n",
       "      <td>2.972000e+01</td>\n",
       "      <td>4.954000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>perimeter_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.072612e+02</td>\n",
       "      <td>3.360254e+01</td>\n",
       "      <td>50.410000</td>\n",
       "      <td>84.110000</td>\n",
       "      <td>97.660000</td>\n",
       "      <td>1.254000e+02</td>\n",
       "      <td>2.512000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>area_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>8.805831e+02</td>\n",
       "      <td>5.693570e+02</td>\n",
       "      <td>185.200000</td>\n",
       "      <td>515.300000</td>\n",
       "      <td>686.500000</td>\n",
       "      <td>1.084000e+03</td>\n",
       "      <td>4.254000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smoothness_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.323686e-01</td>\n",
       "      <td>2.283243e-02</td>\n",
       "      <td>0.071170</td>\n",
       "      <td>0.116600</td>\n",
       "      <td>0.131300</td>\n",
       "      <td>1.460000e-01</td>\n",
       "      <td>2.226000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>compactness_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>2.542650e-01</td>\n",
       "      <td>1.573365e-01</td>\n",
       "      <td>0.027290</td>\n",
       "      <td>0.147200</td>\n",
       "      <td>0.211900</td>\n",
       "      <td>3.391000e-01</td>\n",
       "      <td>1.058000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>concavity_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>2.721885e-01</td>\n",
       "      <td>2.086243e-01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.114500</td>\n",
       "      <td>0.226700</td>\n",
       "      <td>3.829000e-01</td>\n",
       "      <td>1.252000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>concave points_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>1.146062e-01</td>\n",
       "      <td>6.573234e-02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.064930</td>\n",
       "      <td>0.099930</td>\n",
       "      <td>1.614000e-01</td>\n",
       "      <td>2.910000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>symmetry_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>2.900756e-01</td>\n",
       "      <td>6.186747e-02</td>\n",
       "      <td>0.156500</td>\n",
       "      <td>0.250400</td>\n",
       "      <td>0.282200</td>\n",
       "      <td>3.179000e-01</td>\n",
       "      <td>6.638000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fractal_dimension_worst</th>\n",
       "      <td>569.0</td>\n",
       "      <td>8.394582e-02</td>\n",
       "      <td>1.806127e-02</td>\n",
       "      <td>0.055040</td>\n",
       "      <td>0.071460</td>\n",
       "      <td>0.080040</td>\n",
       "      <td>9.208000e-02</td>\n",
       "      <td>2.075000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unnamed: 32</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         count          mean           std          min  \\\n",
       "id                       569.0  3.037183e+07  1.250206e+08  8670.000000   \n",
       "radius_mean              569.0  1.412729e+01  3.524049e+00     6.981000   \n",
       "texture_mean             569.0  1.928965e+01  4.301036e+00     9.710000   \n",
       "perimeter_mean           569.0  9.196903e+01  2.429898e+01    43.790000   \n",
       "area_mean                569.0  6.548891e+02  3.519141e+02   143.500000   \n",
       "smoothness_mean          569.0  9.636028e-02  1.406413e-02     0.052630   \n",
       "compactness_mean         569.0  1.043410e-01  5.281276e-02     0.019380   \n",
       "concavity_mean           569.0  8.879932e-02  7.971981e-02     0.000000   \n",
       "concave points_mean      569.0  4.891915e-02  3.880284e-02     0.000000   \n",
       "symmetry_mean            569.0  1.811619e-01  2.741428e-02     0.106000   \n",
       "fractal_dimension_mean   569.0  6.279761e-02  7.060363e-03     0.049960   \n",
       "radius_se                569.0  4.051721e-01  2.773127e-01     0.111500   \n",
       "texture_se               569.0  1.216853e+00  5.516484e-01     0.360200   \n",
       "perimeter_se             569.0  2.866059e+00  2.021855e+00     0.757000   \n",
       "area_se                  569.0  4.033708e+01  4.549101e+01     6.802000   \n",
       "smoothness_se            569.0  7.040979e-03  3.002518e-03     0.001713   \n",
       "compactness_se           569.0  2.547814e-02  1.790818e-02     0.002252   \n",
       "concavity_se             569.0  3.189372e-02  3.018606e-02     0.000000   \n",
       "concave points_se        569.0  1.179614e-02  6.170285e-03     0.000000   \n",
       "symmetry_se              569.0  2.054230e-02  8.266372e-03     0.007882   \n",
       "fractal_dimension_se     569.0  3.794904e-03  2.646071e-03     0.000895   \n",
       "radius_worst             569.0  1.626919e+01  4.833242e+00     7.930000   \n",
       "texture_worst            569.0  2.567722e+01  6.146258e+00    12.020000   \n",
       "perimeter_worst          569.0  1.072612e+02  3.360254e+01    50.410000   \n",
       "area_worst               569.0  8.805831e+02  5.693570e+02   185.200000   \n",
       "smoothness_worst         569.0  1.323686e-01  2.283243e-02     0.071170   \n",
       "compactness_worst        569.0  2.542650e-01  1.573365e-01     0.027290   \n",
       "concavity_worst          569.0  2.721885e-01  2.086243e-01     0.000000   \n",
       "concave points_worst     569.0  1.146062e-01  6.573234e-02     0.000000   \n",
       "symmetry_worst           569.0  2.900756e-01  6.186747e-02     0.156500   \n",
       "fractal_dimension_worst  569.0  8.394582e-02  1.806127e-02     0.055040   \n",
       "Unnamed: 32                0.0           NaN           NaN          NaN   \n",
       "\n",
       "                                   25%            50%           75%  \\\n",
       "id                       869218.000000  906024.000000  8.813129e+06   \n",
       "radius_mean                  11.700000      13.370000  1.578000e+01   \n",
       "texture_mean                 16.170000      18.840000  2.180000e+01   \n",
       "perimeter_mean               75.170000      86.240000  1.041000e+02   \n",
       "area_mean                   420.300000     551.100000  7.827000e+02   \n",
       "smoothness_mean               0.086370       0.095870  1.053000e-01   \n",
       "compactness_mean              0.064920       0.092630  1.304000e-01   \n",
       "concavity_mean                0.029560       0.061540  1.307000e-01   \n",
       "concave points_mean           0.020310       0.033500  7.400000e-02   \n",
       "symmetry_mean                 0.161900       0.179200  1.957000e-01   \n",
       "fractal_dimension_mean        0.057700       0.061540  6.612000e-02   \n",
       "radius_se                     0.232400       0.324200  4.789000e-01   \n",
       "texture_se                    0.833900       1.108000  1.474000e+00   \n",
       "perimeter_se                  1.606000       2.287000  3.357000e+00   \n",
       "area_se                      17.850000      24.530000  4.519000e+01   \n",
       "smoothness_se                 0.005169       0.006380  8.146000e-03   \n",
       "compactness_se                0.013080       0.020450  3.245000e-02   \n",
       "concavity_se                  0.015090       0.025890  4.205000e-02   \n",
       "concave points_se             0.007638       0.010930  1.471000e-02   \n",
       "symmetry_se                   0.015160       0.018730  2.348000e-02   \n",
       "fractal_dimension_se          0.002248       0.003187  4.558000e-03   \n",
       "radius_worst                 13.010000      14.970000  1.879000e+01   \n",
       "texture_worst                21.080000      25.410000  2.972000e+01   \n",
       "perimeter_worst              84.110000      97.660000  1.254000e+02   \n",
       "area_worst                  515.300000     686.500000  1.084000e+03   \n",
       "smoothness_worst              0.116600       0.131300  1.460000e-01   \n",
       "compactness_worst             0.147200       0.211900  3.391000e-01   \n",
       "concavity_worst               0.114500       0.226700  3.829000e-01   \n",
       "concave points_worst          0.064930       0.099930  1.614000e-01   \n",
       "symmetry_worst                0.250400       0.282200  3.179000e-01   \n",
       "fractal_dimension_worst       0.071460       0.080040  9.208000e-02   \n",
       "Unnamed: 32                        NaN            NaN           NaN   \n",
       "\n",
       "                                  max  \n",
       "id                       9.113205e+08  \n",
       "radius_mean              2.811000e+01  \n",
       "texture_mean             3.928000e+01  \n",
       "perimeter_mean           1.885000e+02  \n",
       "area_mean                2.501000e+03  \n",
       "smoothness_mean          1.634000e-01  \n",
       "compactness_mean         3.454000e-01  \n",
       "concavity_mean           4.268000e-01  \n",
       "concave points_mean      2.012000e-01  \n",
       "symmetry_mean            3.040000e-01  \n",
       "fractal_dimension_mean   9.744000e-02  \n",
       "radius_se                2.873000e+00  \n",
       "texture_se               4.885000e+00  \n",
       "perimeter_se             2.198000e+01  \n",
       "area_se                  5.422000e+02  \n",
       "smoothness_se            3.113000e-02  \n",
       "compactness_se           1.354000e-01  \n",
       "concavity_se             3.960000e-01  \n",
       "concave points_se        5.279000e-02  \n",
       "symmetry_se              7.895000e-02  \n",
       "fractal_dimension_se     2.984000e-02  \n",
       "radius_worst             3.604000e+01  \n",
       "texture_worst            4.954000e+01  \n",
       "perimeter_worst          2.512000e+02  \n",
       "area_worst               4.254000e+03  \n",
       "smoothness_worst         2.226000e-01  \n",
       "compactness_worst        1.058000e+00  \n",
       "concavity_worst          1.252000e+00  \n",
       "concave points_worst     2.910000e-01  \n",
       "symmetry_worst           6.638000e-01  \n",
       "fractal_dimension_worst  2.075000e-01  \n",
       "Unnamed: 32                       NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 569 entries, 0 to 568\n",
      "Data columns (total 33 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   id                       569 non-null    int64  \n",
      " 1   diagnosis                569 non-null    object \n",
      " 2   radius_mean              569 non-null    float64\n",
      " 3   texture_mean             569 non-null    float64\n",
      " 4   perimeter_mean           569 non-null    float64\n",
      " 5   area_mean                569 non-null    float64\n",
      " 6   smoothness_mean          569 non-null    float64\n",
      " 7   compactness_mean         569 non-null    float64\n",
      " 8   concavity_mean           569 non-null    float64\n",
      " 9   concave points_mean      569 non-null    float64\n",
      " 10  symmetry_mean            569 non-null    float64\n",
      " 11  fractal_dimension_mean   569 non-null    float64\n",
      " 12  radius_se                569 non-null    float64\n",
      " 13  texture_se               569 non-null    float64\n",
      " 14  perimeter_se             569 non-null    float64\n",
      " 15  area_se                  569 non-null    float64\n",
      " 16  smoothness_se            569 non-null    float64\n",
      " 17  compactness_se           569 non-null    float64\n",
      " 18  concavity_se             569 non-null    float64\n",
      " 19  concave points_se        569 non-null    float64\n",
      " 20  symmetry_se              569 non-null    float64\n",
      " 21  fractal_dimension_se     569 non-null    float64\n",
      " 22  radius_worst             569 non-null    float64\n",
      " 23  texture_worst            569 non-null    float64\n",
      " 24  perimeter_worst          569 non-null    float64\n",
      " 25  area_worst               569 non-null    float64\n",
      " 26  smoothness_worst         569 non-null    float64\n",
      " 27  compactness_worst        569 non-null    float64\n",
      " 28  concavity_worst          569 non-null    float64\n",
      " 29  concave points_worst     569 non-null    float64\n",
      " 30  symmetry_worst           569 non-null    float64\n",
      " 31  fractal_dimension_worst  569 non-null    float64\n",
      " 32  Unnamed: 32              0 non-null      float64\n",
      "dtypes: float64(31), int64(1), object(1)\n",
      "memory usage: 146.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['Unnamed: 32'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***********************************************\n",
    "### Machine Learning Model Selection, Training and Tuning  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### PyCaret\n",
    "\n",
    "PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the experiment cycle exponentially and makes you more productive.  \n",
    "\n",
    "In comparison with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few words only. This makes experiments exponentially fast and efficient. PyCaret is essentially a Python wrapper around several machine learning libraries and frameworks such as scikit-learn, XGBoost, LightGBM, CatBoost, spaCy, Optuna, Hyperopt, Ray, and many more.  \n",
    "\n",
    "(Source: https://pycaret.readthedocs.io/en/latest/index.html)  \n",
    "\n",
    "**Functions used**  \n",
    "* `setup` - initializes the environment in pycaret and creates the transformation pipeline to prepare the data for modeling and deployment.  \n",
    "* `compare_models` - trains all models in the model library and scores them using stratified cross validation for metric evaluation.  \n",
    "* `create_model` - trains and evaluates a model using cross validation.  \n",
    "* `tune_model` - automatically tunes the hyperparameters of a model using Random Grid Search on a pre-defined search space.  \n",
    "* `plot_model` - used to analyze the performance across different aspects such as AUC, confusion_matrix, decision boundary etc. This function takes a trained model object and returns a plot based on the test / hold-out set.  \n",
    "* `predict_model` - predict against the hold-out sample and evaluate the metrics to see if they are materially different than the CV results.  \n",
    "\n",
    "#### Initialize PyCaret"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_ccbe4_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Description</th>        <th class=\"col_heading level0 col1\" >Value</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_ccbe4_row0_col0\" class=\"data row0 col0\" >session_id</td>\n",
       "                        <td id=\"T_ccbe4_row0_col1\" class=\"data row0 col1\" >2441</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_ccbe4_row1_col0\" class=\"data row1 col0\" >Target</td>\n",
       "                        <td id=\"T_ccbe4_row1_col1\" class=\"data row1 col1\" >diagnosis</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_ccbe4_row2_col0\" class=\"data row2 col0\" >Target Type</td>\n",
       "                        <td id=\"T_ccbe4_row2_col1\" class=\"data row2 col1\" >Binary</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_ccbe4_row3_col0\" class=\"data row3 col0\" >Label Encoded</td>\n",
       "                        <td id=\"T_ccbe4_row3_col1\" class=\"data row3 col1\" >B: 0, M: 1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_ccbe4_row4_col0\" class=\"data row4 col0\" >Original Data</td>\n",
       "                        <td id=\"T_ccbe4_row4_col1\" class=\"data row4 col1\" >(569, 32)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_ccbe4_row5_col0\" class=\"data row5 col0\" >Missing Values</td>\n",
       "                        <td id=\"T_ccbe4_row5_col1\" class=\"data row5 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_ccbe4_row6_col0\" class=\"data row6 col0\" >Numeric Features</td>\n",
       "                        <td id=\"T_ccbe4_row6_col1\" class=\"data row6 col1\" >31</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_ccbe4_row7_col0\" class=\"data row7 col0\" >Categorical Features</td>\n",
       "                        <td id=\"T_ccbe4_row7_col1\" class=\"data row7 col1\" >0</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_ccbe4_row8_col0\" class=\"data row8 col0\" >Ordinal Features</td>\n",
       "                        <td id=\"T_ccbe4_row8_col1\" class=\"data row8 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_ccbe4_row9_col0\" class=\"data row9 col0\" >High Cardinality Features</td>\n",
       "                        <td id=\"T_ccbe4_row9_col1\" class=\"data row9 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_ccbe4_row10_col0\" class=\"data row10 col0\" >High Cardinality Method</td>\n",
       "                        <td id=\"T_ccbe4_row10_col1\" class=\"data row10 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_ccbe4_row11_col0\" class=\"data row11 col0\" >Transformed Train Set</td>\n",
       "                        <td id=\"T_ccbe4_row11_col1\" class=\"data row11 col1\" >(398, 30)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_ccbe4_row12_col0\" class=\"data row12 col0\" >Transformed Test Set</td>\n",
       "                        <td id=\"T_ccbe4_row12_col1\" class=\"data row12 col1\" >(171, 30)</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_ccbe4_row13_col0\" class=\"data row13 col0\" >Shuffle Train-Test</td>\n",
       "                        <td id=\"T_ccbe4_row13_col1\" class=\"data row13 col1\" >True</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_ccbe4_row14_col0\" class=\"data row14 col0\" >Stratify Train-Test</td>\n",
       "                        <td id=\"T_ccbe4_row14_col1\" class=\"data row14 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_ccbe4_row15_col0\" class=\"data row15 col0\" >Fold Generator</td>\n",
       "                        <td id=\"T_ccbe4_row15_col1\" class=\"data row15 col1\" >StratifiedKFold</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_ccbe4_row16_col0\" class=\"data row16 col0\" >Fold Number</td>\n",
       "                        <td id=\"T_ccbe4_row16_col1\" class=\"data row16 col1\" >10</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_ccbe4_row17_col0\" class=\"data row17 col0\" >CPU Jobs</td>\n",
       "                        <td id=\"T_ccbe4_row17_col1\" class=\"data row17 col1\" >-1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_ccbe4_row18_col0\" class=\"data row18 col0\" >Use GPU</td>\n",
       "                        <td id=\"T_ccbe4_row18_col1\" class=\"data row18 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_ccbe4_row19_col0\" class=\"data row19 col0\" >Log Experiment</td>\n",
       "                        <td id=\"T_ccbe4_row19_col1\" class=\"data row19 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_ccbe4_row20_col0\" class=\"data row20 col0\" >Experiment Name</td>\n",
       "                        <td id=\"T_ccbe4_row20_col1\" class=\"data row20 col1\" >clf-default-name</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_ccbe4_row21_col0\" class=\"data row21 col0\" >USI</td>\n",
       "                        <td id=\"T_ccbe4_row21_col1\" class=\"data row21 col1\" >a317</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_ccbe4_row22_col0\" class=\"data row22 col0\" >Imputation Type</td>\n",
       "                        <td id=\"T_ccbe4_row22_col1\" class=\"data row22 col1\" >simple</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_ccbe4_row23_col0\" class=\"data row23 col0\" >Iterative Imputation Iteration</td>\n",
       "                        <td id=\"T_ccbe4_row23_col1\" class=\"data row23 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_ccbe4_row24_col0\" class=\"data row24 col0\" >Numeric Imputer</td>\n",
       "                        <td id=\"T_ccbe4_row24_col1\" class=\"data row24 col1\" >mean</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_ccbe4_row25_col0\" class=\"data row25 col0\" >Iterative Imputation Numeric Model</td>\n",
       "                        <td id=\"T_ccbe4_row25_col1\" class=\"data row25 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_ccbe4_row26_col0\" class=\"data row26 col0\" >Categorical Imputer</td>\n",
       "                        <td id=\"T_ccbe4_row26_col1\" class=\"data row26 col1\" >constant</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_ccbe4_row27_col0\" class=\"data row27 col0\" >Iterative Imputation Categorical Model</td>\n",
       "                        <td id=\"T_ccbe4_row27_col1\" class=\"data row27 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_ccbe4_row28_col0\" class=\"data row28 col0\" >Unknown Categoricals Handling</td>\n",
       "                        <td id=\"T_ccbe4_row28_col1\" class=\"data row28 col1\" >least_frequent</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_ccbe4_row29_col0\" class=\"data row29 col0\" >Normalize</td>\n",
       "                        <td id=\"T_ccbe4_row29_col1\" class=\"data row29 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
       "                        <td id=\"T_ccbe4_row30_col0\" class=\"data row30 col0\" >Normalize Method</td>\n",
       "                        <td id=\"T_ccbe4_row30_col1\" class=\"data row30 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
       "                        <td id=\"T_ccbe4_row31_col0\" class=\"data row31 col0\" >Transformation</td>\n",
       "                        <td id=\"T_ccbe4_row31_col1\" class=\"data row31 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
       "                        <td id=\"T_ccbe4_row32_col0\" class=\"data row32 col0\" >Transformation Method</td>\n",
       "                        <td id=\"T_ccbe4_row32_col1\" class=\"data row32 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
       "                        <td id=\"T_ccbe4_row33_col0\" class=\"data row33 col0\" >PCA</td>\n",
       "                        <td id=\"T_ccbe4_row33_col1\" class=\"data row33 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
       "                        <td id=\"T_ccbe4_row34_col0\" class=\"data row34 col0\" >PCA Method</td>\n",
       "                        <td id=\"T_ccbe4_row34_col1\" class=\"data row34 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
       "                        <td id=\"T_ccbe4_row35_col0\" class=\"data row35 col0\" >PCA Components</td>\n",
       "                        <td id=\"T_ccbe4_row35_col1\" class=\"data row35 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
       "                        <td id=\"T_ccbe4_row36_col0\" class=\"data row36 col0\" >Ignore Low Variance</td>\n",
       "                        <td id=\"T_ccbe4_row36_col1\" class=\"data row36 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
       "                        <td id=\"T_ccbe4_row37_col0\" class=\"data row37 col0\" >Combine Rare Levels</td>\n",
       "                        <td id=\"T_ccbe4_row37_col1\" class=\"data row37 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
       "                        <td id=\"T_ccbe4_row38_col0\" class=\"data row38 col0\" >Rare Level Threshold</td>\n",
       "                        <td id=\"T_ccbe4_row38_col1\" class=\"data row38 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
       "                        <td id=\"T_ccbe4_row39_col0\" class=\"data row39 col0\" >Numeric Binning</td>\n",
       "                        <td id=\"T_ccbe4_row39_col1\" class=\"data row39 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
       "                        <td id=\"T_ccbe4_row40_col0\" class=\"data row40 col0\" >Remove Outliers</td>\n",
       "                        <td id=\"T_ccbe4_row40_col1\" class=\"data row40 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
       "                        <td id=\"T_ccbe4_row41_col0\" class=\"data row41 col0\" >Outliers Threshold</td>\n",
       "                        <td id=\"T_ccbe4_row41_col1\" class=\"data row41 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
       "                        <td id=\"T_ccbe4_row42_col0\" class=\"data row42 col0\" >Remove Multicollinearity</td>\n",
       "                        <td id=\"T_ccbe4_row42_col1\" class=\"data row42 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
       "                        <td id=\"T_ccbe4_row43_col0\" class=\"data row43 col0\" >Multicollinearity Threshold</td>\n",
       "                        <td id=\"T_ccbe4_row43_col1\" class=\"data row43 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
       "                        <td id=\"T_ccbe4_row44_col0\" class=\"data row44 col0\" >Clustering</td>\n",
       "                        <td id=\"T_ccbe4_row44_col1\" class=\"data row44 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
       "                        <td id=\"T_ccbe4_row45_col0\" class=\"data row45 col0\" >Clustering Iteration</td>\n",
       "                        <td id=\"T_ccbe4_row45_col1\" class=\"data row45 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
       "                        <td id=\"T_ccbe4_row46_col0\" class=\"data row46 col0\" >Polynomial Features</td>\n",
       "                        <td id=\"T_ccbe4_row46_col1\" class=\"data row46 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
       "                        <td id=\"T_ccbe4_row47_col0\" class=\"data row47 col0\" >Polynomial Degree</td>\n",
       "                        <td id=\"T_ccbe4_row47_col1\" class=\"data row47 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
       "                        <td id=\"T_ccbe4_row48_col0\" class=\"data row48 col0\" >Trignometry Features</td>\n",
       "                        <td id=\"T_ccbe4_row48_col1\" class=\"data row48 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
       "                        <td id=\"T_ccbe4_row49_col0\" class=\"data row49 col0\" >Polynomial Threshold</td>\n",
       "                        <td id=\"T_ccbe4_row49_col1\" class=\"data row49 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
       "                        <td id=\"T_ccbe4_row50_col0\" class=\"data row50 col0\" >Group Features</td>\n",
       "                        <td id=\"T_ccbe4_row50_col1\" class=\"data row50 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
       "                        <td id=\"T_ccbe4_row51_col0\" class=\"data row51 col0\" >Feature Selection</td>\n",
       "                        <td id=\"T_ccbe4_row51_col1\" class=\"data row51 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
       "                        <td id=\"T_ccbe4_row52_col0\" class=\"data row52 col0\" >Feature Selection Method</td>\n",
       "                        <td id=\"T_ccbe4_row52_col1\" class=\"data row52 col1\" >classic</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
       "                        <td id=\"T_ccbe4_row53_col0\" class=\"data row53 col0\" >Features Selection Threshold</td>\n",
       "                        <td id=\"T_ccbe4_row53_col1\" class=\"data row53 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
       "                        <td id=\"T_ccbe4_row54_col0\" class=\"data row54 col0\" >Feature Interaction</td>\n",
       "                        <td id=\"T_ccbe4_row54_col1\" class=\"data row54 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
       "                        <td id=\"T_ccbe4_row55_col0\" class=\"data row55 col0\" >Feature Ratio</td>\n",
       "                        <td id=\"T_ccbe4_row55_col1\" class=\"data row55 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
       "                        <td id=\"T_ccbe4_row56_col0\" class=\"data row56 col0\" >Interaction Threshold</td>\n",
       "                        <td id=\"T_ccbe4_row56_col1\" class=\"data row56 col1\" >None</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
       "                        <td id=\"T_ccbe4_row57_col0\" class=\"data row57 col0\" >Fix Imbalance</td>\n",
       "                        <td id=\"T_ccbe4_row57_col1\" class=\"data row57 col1\" >False</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ccbe4_level0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
       "                        <td id=\"T_ccbe4_row58_col0\" class=\"data row58 col0\" >Fix Imbalance Method</td>\n",
       "                        <td id=\"T_ccbe4_row58_col1\" class=\"data row58 col1\" >SMOTE</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1a5fc3d3ee0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clf1 = setup(df, target = 'diagnosis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Compare Baseline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        }</style><table id=\"T_60a30_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Model</th>        <th class=\"col_heading level0 col1\" >Accuracy</th>        <th class=\"col_heading level0 col2\" >AUC</th>        <th class=\"col_heading level0 col3\" >Recall</th>        <th class=\"col_heading level0 col4\" >Prec.</th>        <th class=\"col_heading level0 col5\" >F1</th>        <th class=\"col_heading level0 col6\" >Kappa</th>        <th class=\"col_heading level0 col7\" >MCC</th>        <th class=\"col_heading level0 col8\" >TT (Sec)</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_60a30_level0_row0\" class=\"row_heading level0 row0\" >catboost</th>\n",
       "                        <td id=\"T_60a30_row0_col0\" class=\"data row0 col0\" >CatBoost Classifier</td>\n",
       "                        <td id=\"T_60a30_row0_col1\" class=\"data row0 col1\" >0.9724</td>\n",
       "                        <td id=\"T_60a30_row0_col2\" class=\"data row0 col2\" >0.9967</td>\n",
       "                        <td id=\"T_60a30_row0_col3\" class=\"data row0 col3\" >0.9500</td>\n",
       "                        <td id=\"T_60a30_row0_col4\" class=\"data row0 col4\" >0.9729</td>\n",
       "                        <td id=\"T_60a30_row0_col5\" class=\"data row0 col5\" >0.9594</td>\n",
       "                        <td id=\"T_60a30_row0_col6\" class=\"data row0 col6\" >0.9386</td>\n",
       "                        <td id=\"T_60a30_row0_col7\" class=\"data row0 col7\" >0.9408</td>\n",
       "                        <td id=\"T_60a30_row0_col8\" class=\"data row0 col8\" >2.4360</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row1\" class=\"row_heading level0 row1\" >xgboost</th>\n",
       "                        <td id=\"T_60a30_row1_col0\" class=\"data row1 col0\" >Extreme Gradient Boosting</td>\n",
       "                        <td id=\"T_60a30_row1_col1\" class=\"data row1 col1\" >0.9650</td>\n",
       "                        <td id=\"T_60a30_row1_col2\" class=\"data row1 col2\" >0.9956</td>\n",
       "                        <td id=\"T_60a30_row1_col3\" class=\"data row1 col3\" >0.9429</td>\n",
       "                        <td id=\"T_60a30_row1_col4\" class=\"data row1 col4\" >0.9571</td>\n",
       "                        <td id=\"T_60a30_row1_col5\" class=\"data row1 col5\" >0.9479</td>\n",
       "                        <td id=\"T_60a30_row1_col6\" class=\"data row1 col6\" >0.9217</td>\n",
       "                        <td id=\"T_60a30_row1_col7\" class=\"data row1 col7\" >0.9238</td>\n",
       "                        <td id=\"T_60a30_row1_col8\" class=\"data row1 col8\" >0.0550</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row2\" class=\"row_heading level0 row2\" >ada</th>\n",
       "                        <td id=\"T_60a30_row2_col0\" class=\"data row2 col0\" >Ada Boost Classifier</td>\n",
       "                        <td id=\"T_60a30_row2_col1\" class=\"data row2 col1\" >0.9648</td>\n",
       "                        <td id=\"T_60a30_row2_col2\" class=\"data row2 col2\" >0.9923</td>\n",
       "                        <td id=\"T_60a30_row2_col3\" class=\"data row2 col3\" >0.9352</td>\n",
       "                        <td id=\"T_60a30_row2_col4\" class=\"data row2 col4\" >0.9647</td>\n",
       "                        <td id=\"T_60a30_row2_col5\" class=\"data row2 col5\" >0.9478</td>\n",
       "                        <td id=\"T_60a30_row2_col6\" class=\"data row2 col6\" >0.9213</td>\n",
       "                        <td id=\"T_60a30_row2_col7\" class=\"data row2 col7\" >0.9236</td>\n",
       "                        <td id=\"T_60a30_row2_col8\" class=\"data row2 col8\" >0.0230</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row3\" class=\"row_heading level0 row3\" >lda</th>\n",
       "                        <td id=\"T_60a30_row3_col0\" class=\"data row3 col0\" >Linear Discriminant Analysis</td>\n",
       "                        <td id=\"T_60a30_row3_col1\" class=\"data row3 col1\" >0.9648</td>\n",
       "                        <td id=\"T_60a30_row3_col2\" class=\"data row3 col2\" >0.9880</td>\n",
       "                        <td id=\"T_60a30_row3_col3\" class=\"data row3 col3\" >0.9060</td>\n",
       "                        <td id=\"T_60a30_row3_col4\" class=\"data row3 col4\" >0.9917</td>\n",
       "                        <td id=\"T_60a30_row3_col5\" class=\"data row3 col5\" >0.9458</td>\n",
       "                        <td id=\"T_60a30_row3_col6\" class=\"data row3 col6\" >0.9199</td>\n",
       "                        <td id=\"T_60a30_row3_col7\" class=\"data row3 col7\" >0.9231</td>\n",
       "                        <td id=\"T_60a30_row3_col8\" class=\"data row3 col8\" >0.0050</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row4\" class=\"row_heading level0 row4\" >et</th>\n",
       "                        <td id=\"T_60a30_row4_col0\" class=\"data row4 col0\" >Extra Trees Classifier</td>\n",
       "                        <td id=\"T_60a30_row4_col1\" class=\"data row4 col1\" >0.9647</td>\n",
       "                        <td id=\"T_60a30_row4_col2\" class=\"data row4 col2\" >0.9968</td>\n",
       "                        <td id=\"T_60a30_row4_col3\" class=\"data row4 col3\" >0.9352</td>\n",
       "                        <td id=\"T_60a30_row4_col4\" class=\"data row4 col4\" >0.9648</td>\n",
       "                        <td id=\"T_60a30_row4_col5\" class=\"data row4 col5\" >0.9481</td>\n",
       "                        <td id=\"T_60a30_row4_col6\" class=\"data row4 col6\" >0.9215</td>\n",
       "                        <td id=\"T_60a30_row4_col7\" class=\"data row4 col7\" >0.9235</td>\n",
       "                        <td id=\"T_60a30_row4_col8\" class=\"data row4 col8\" >0.0600</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row5\" class=\"row_heading level0 row5\" >gbc</th>\n",
       "                        <td id=\"T_60a30_row5_col0\" class=\"data row5 col0\" >Gradient Boosting Classifier</td>\n",
       "                        <td id=\"T_60a30_row5_col1\" class=\"data row5 col1\" >0.9623</td>\n",
       "                        <td id=\"T_60a30_row5_col2\" class=\"data row5 col2\" >0.9945</td>\n",
       "                        <td id=\"T_60a30_row5_col3\" class=\"data row5 col3\" >0.9429</td>\n",
       "                        <td id=\"T_60a30_row5_col4\" class=\"data row5 col4\" >0.9529</td>\n",
       "                        <td id=\"T_60a30_row5_col5\" class=\"data row5 col5\" >0.9451</td>\n",
       "                        <td id=\"T_60a30_row5_col6\" class=\"data row5 col6\" >0.9165</td>\n",
       "                        <td id=\"T_60a30_row5_col7\" class=\"data row5 col7\" >0.9195</td>\n",
       "                        <td id=\"T_60a30_row5_col8\" class=\"data row5 col8\" >0.0460</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row6\" class=\"row_heading level0 row6\" >qda</th>\n",
       "                        <td id=\"T_60a30_row6_col0\" class=\"data row6 col0\" >Quadratic Discriminant Analysis</td>\n",
       "                        <td id=\"T_60a30_row6_col1\" class=\"data row6 col1\" >0.9622</td>\n",
       "                        <td id=\"T_60a30_row6_col2\" class=\"data row6 col2\" >0.9935</td>\n",
       "                        <td id=\"T_60a30_row6_col3\" class=\"data row6 col3\" >0.9643</td>\n",
       "                        <td id=\"T_60a30_row6_col4\" class=\"data row6 col4\" >0.9336</td>\n",
       "                        <td id=\"T_60a30_row6_col5\" class=\"data row6 col5\" >0.9473</td>\n",
       "                        <td id=\"T_60a30_row6_col6\" class=\"data row6 col6\" >0.9180</td>\n",
       "                        <td id=\"T_60a30_row6_col7\" class=\"data row6 col7\" >0.9199</td>\n",
       "                        <td id=\"T_60a30_row6_col8\" class=\"data row6 col8\" >0.0050</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row7\" class=\"row_heading level0 row7\" >ridge</th>\n",
       "                        <td id=\"T_60a30_row7_col0\" class=\"data row7 col0\" >Ridge Classifier</td>\n",
       "                        <td id=\"T_60a30_row7_col1\" class=\"data row7 col1\" >0.9597</td>\n",
       "                        <td id=\"T_60a30_row7_col2\" class=\"data row7 col2\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row7_col3\" class=\"data row7 col3\" >0.8989</td>\n",
       "                        <td id=\"T_60a30_row7_col4\" class=\"data row7 col4\" >0.9846</td>\n",
       "                        <td id=\"T_60a30_row7_col5\" class=\"data row7 col5\" >0.9384</td>\n",
       "                        <td id=\"T_60a30_row7_col6\" class=\"data row7 col6\" >0.9087</td>\n",
       "                        <td id=\"T_60a30_row7_col7\" class=\"data row7 col7\" >0.9122</td>\n",
       "                        <td id=\"T_60a30_row7_col8\" class=\"data row7 col8\" >0.0150</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row8\" class=\"row_heading level0 row8\" >lightgbm</th>\n",
       "                        <td id=\"T_60a30_row8_col0\" class=\"data row8 col0\" >Light Gradient Boosting Machine</td>\n",
       "                        <td id=\"T_60a30_row8_col1\" class=\"data row8 col1\" >0.9597</td>\n",
       "                        <td id=\"T_60a30_row8_col2\" class=\"data row8 col2\" >0.9958</td>\n",
       "                        <td id=\"T_60a30_row8_col3\" class=\"data row8 col3\" >0.9280</td>\n",
       "                        <td id=\"T_60a30_row8_col4\" class=\"data row8 col4\" >0.9581</td>\n",
       "                        <td id=\"T_60a30_row8_col5\" class=\"data row8 col5\" >0.9407</td>\n",
       "                        <td id=\"T_60a30_row8_col6\" class=\"data row8 col6\" >0.9103</td>\n",
       "                        <td id=\"T_60a30_row8_col7\" class=\"data row8 col7\" >0.9129</td>\n",
       "                        <td id=\"T_60a30_row8_col8\" class=\"data row8 col8\" >0.2210</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row9\" class=\"row_heading level0 row9\" >rf</th>\n",
       "                        <td id=\"T_60a30_row9_col0\" class=\"data row9 col0\" >Random Forest Classifier</td>\n",
       "                        <td id=\"T_60a30_row9_col1\" class=\"data row9 col1\" >0.9522</td>\n",
       "                        <td id=\"T_60a30_row9_col2\" class=\"data row9 col2\" >0.9917</td>\n",
       "                        <td id=\"T_60a30_row9_col3\" class=\"data row9 col3\" >0.9286</td>\n",
       "                        <td id=\"T_60a30_row9_col4\" class=\"data row9 col4\" >0.9383</td>\n",
       "                        <td id=\"T_60a30_row9_col5\" class=\"data row9 col5\" >0.9306</td>\n",
       "                        <td id=\"T_60a30_row9_col6\" class=\"data row9 col6\" >0.8943</td>\n",
       "                        <td id=\"T_60a30_row9_col7\" class=\"data row9 col7\" >0.8975</td>\n",
       "                        <td id=\"T_60a30_row9_col8\" class=\"data row9 col8\" >0.0620</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row10\" class=\"row_heading level0 row10\" >dt</th>\n",
       "                        <td id=\"T_60a30_row10_col0\" class=\"data row10 col0\" >Decision Tree Classifier</td>\n",
       "                        <td id=\"T_60a30_row10_col1\" class=\"data row10 col1\" >0.9221</td>\n",
       "                        <td id=\"T_60a30_row10_col2\" class=\"data row10 col2\" >0.9173</td>\n",
       "                        <td id=\"T_60a30_row10_col3\" class=\"data row10 col3\" >0.9000</td>\n",
       "                        <td id=\"T_60a30_row10_col4\" class=\"data row10 col4\" >0.8840</td>\n",
       "                        <td id=\"T_60a30_row10_col5\" class=\"data row10 col5\" >0.8878</td>\n",
       "                        <td id=\"T_60a30_row10_col6\" class=\"data row10 col6\" >0.8285</td>\n",
       "                        <td id=\"T_60a30_row10_col7\" class=\"data row10 col7\" >0.8330</td>\n",
       "                        <td id=\"T_60a30_row10_col8\" class=\"data row10 col8\" >0.0080</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row11\" class=\"row_heading level0 row11\" >knn</th>\n",
       "                        <td id=\"T_60a30_row11_col0\" class=\"data row11 col0\" >K Neighbors Classifier</td>\n",
       "                        <td id=\"T_60a30_row11_col1\" class=\"data row11 col1\" >0.7110</td>\n",
       "                        <td id=\"T_60a30_row11_col2\" class=\"data row11 col2\" >0.7603</td>\n",
       "                        <td id=\"T_60a30_row11_col3\" class=\"data row11 col3\" >0.4341</td>\n",
       "                        <td id=\"T_60a30_row11_col4\" class=\"data row11 col4\" >0.6252</td>\n",
       "                        <td id=\"T_60a30_row11_col5\" class=\"data row11 col5\" >0.5092</td>\n",
       "                        <td id=\"T_60a30_row11_col6\" class=\"data row11 col6\" >0.3139</td>\n",
       "                        <td id=\"T_60a30_row11_col7\" class=\"data row11 col7\" >0.3264</td>\n",
       "                        <td id=\"T_60a30_row11_col8\" class=\"data row11 col8\" >0.0180</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row12\" class=\"row_heading level0 row12\" >lr</th>\n",
       "                        <td id=\"T_60a30_row12_col0\" class=\"data row12 col0\" >Logistic Regression</td>\n",
       "                        <td id=\"T_60a30_row12_col1\" class=\"data row12 col1\" >0.6533</td>\n",
       "                        <td id=\"T_60a30_row12_col2\" class=\"data row12 col2\" >0.5480</td>\n",
       "                        <td id=\"T_60a30_row12_col3\" class=\"data row12 col3\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row12_col4\" class=\"data row12 col4\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row12_col5\" class=\"data row12 col5\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row12_col6\" class=\"data row12 col6\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row12_col7\" class=\"data row12 col7\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row12_col8\" class=\"data row12 col8\" >0.6560</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row13\" class=\"row_heading level0 row13\" >nb</th>\n",
       "                        <td id=\"T_60a30_row13_col0\" class=\"data row13 col0\" >Naive Bayes</td>\n",
       "                        <td id=\"T_60a30_row13_col1\" class=\"data row13 col1\" >0.6483</td>\n",
       "                        <td id=\"T_60a30_row13_col2\" class=\"data row13 col2\" >0.8944</td>\n",
       "                        <td id=\"T_60a30_row13_col3\" class=\"data row13 col3\" >0.0148</td>\n",
       "                        <td id=\"T_60a30_row13_col4\" class=\"data row13 col4\" >0.1500</td>\n",
       "                        <td id=\"T_60a30_row13_col5\" class=\"data row13 col5\" >0.0267</td>\n",
       "                        <td id=\"T_60a30_row13_col6\" class=\"data row13 col6\" >-0.0007</td>\n",
       "                        <td id=\"T_60a30_row13_col7\" class=\"data row13 col7\" >-0.0052</td>\n",
       "                        <td id=\"T_60a30_row13_col8\" class=\"data row13 col8\" >0.0030</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_60a30_level0_row14\" class=\"row_heading level0 row14\" >svm</th>\n",
       "                        <td id=\"T_60a30_row14_col0\" class=\"data row14 col0\" >SVM - Linear Kernel</td>\n",
       "                        <td id=\"T_60a30_row14_col1\" class=\"data row14 col1\" >0.5600</td>\n",
       "                        <td id=\"T_60a30_row14_col2\" class=\"data row14 col2\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row14_col3\" class=\"data row14 col3\" >0.3000</td>\n",
       "                        <td id=\"T_60a30_row14_col4\" class=\"data row14 col4\" >0.1033</td>\n",
       "                        <td id=\"T_60a30_row14_col5\" class=\"data row14 col5\" >0.1537</td>\n",
       "                        <td id=\"T_60a30_row14_col6\" class=\"data row14 col6\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row14_col7\" class=\"data row14 col7\" >0.0000</td>\n",
       "                        <td id=\"T_60a30_row14_col8\" class=\"data row14 col8\" >0.0160</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1a5fc26fb20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 41.5 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "best_model = compare_models()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create best model from baseline results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_95580_row10_col0,#T_95580_row10_col1,#T_95580_row10_col2,#T_95580_row10_col3,#T_95580_row10_col4,#T_95580_row10_col5,#T_95580_row10_col6{\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_95580_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_95580_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_95580_row0_col0\" class=\"data row0 col0\" >0.9500</td>\n",
       "                        <td id=\"T_95580_row0_col1\" class=\"data row0 col1\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row0_col2\" class=\"data row0 col2\" >0.8571</td>\n",
       "                        <td id=\"T_95580_row0_col3\" class=\"data row0 col3\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row0_col4\" class=\"data row0 col4\" >0.9231</td>\n",
       "                        <td id=\"T_95580_row0_col5\" class=\"data row0 col5\" >0.8864</td>\n",
       "                        <td id=\"T_95580_row0_col6\" class=\"data row0 col6\" >0.8921</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_95580_row1_col0\" class=\"data row1 col0\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row1_col1\" class=\"data row1 col1\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row1_col2\" class=\"data row1 col2\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row1_col3\" class=\"data row1 col3\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row1_col4\" class=\"data row1 col4\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row1_col5\" class=\"data row1 col5\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row1_col6\" class=\"data row1 col6\" >1.0000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_95580_row2_col0\" class=\"data row2 col0\" >0.9750</td>\n",
       "                        <td id=\"T_95580_row2_col1\" class=\"data row2 col1\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row2_col2\" class=\"data row2 col2\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row2_col3\" class=\"data row2 col3\" >0.9333</td>\n",
       "                        <td id=\"T_95580_row2_col4\" class=\"data row2 col4\" >0.9655</td>\n",
       "                        <td id=\"T_95580_row2_col5\" class=\"data row2 col5\" >0.9459</td>\n",
       "                        <td id=\"T_95580_row2_col6\" class=\"data row2 col6\" >0.9473</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_95580_row3_col0\" class=\"data row3 col0\" >0.9500</td>\n",
       "                        <td id=\"T_95580_row3_col1\" class=\"data row3 col1\" >0.9863</td>\n",
       "                        <td id=\"T_95580_row3_col2\" class=\"data row3 col2\" >0.8571</td>\n",
       "                        <td id=\"T_95580_row3_col3\" class=\"data row3 col3\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row3_col4\" class=\"data row3 col4\" >0.9231</td>\n",
       "                        <td id=\"T_95580_row3_col5\" class=\"data row3 col5\" >0.8864</td>\n",
       "                        <td id=\"T_95580_row3_col6\" class=\"data row3 col6\" >0.8921</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_95580_row4_col0\" class=\"data row4 col0\" >0.9500</td>\n",
       "                        <td id=\"T_95580_row4_col1\" class=\"data row4 col1\" >0.9945</td>\n",
       "                        <td id=\"T_95580_row4_col2\" class=\"data row4 col2\" >0.8571</td>\n",
       "                        <td id=\"T_95580_row4_col3\" class=\"data row4 col3\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row4_col4\" class=\"data row4 col4\" >0.9231</td>\n",
       "                        <td id=\"T_95580_row4_col5\" class=\"data row4 col5\" >0.8864</td>\n",
       "                        <td id=\"T_95580_row4_col6\" class=\"data row4 col6\" >0.8921</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_95580_row5_col0\" class=\"data row5 col0\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row5_col1\" class=\"data row5 col1\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row5_col2\" class=\"data row5 col2\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row5_col3\" class=\"data row5 col3\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row5_col4\" class=\"data row5 col4\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row5_col5\" class=\"data row5 col5\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row5_col6\" class=\"data row5 col6\" >1.0000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_95580_row6_col0\" class=\"data row6 col0\" >0.9250</td>\n",
       "                        <td id=\"T_95580_row6_col1\" class=\"data row6 col1\" >0.9890</td>\n",
       "                        <td id=\"T_95580_row6_col2\" class=\"data row6 col2\" >0.9286</td>\n",
       "                        <td id=\"T_95580_row6_col3\" class=\"data row6 col3\" >0.8667</td>\n",
       "                        <td id=\"T_95580_row6_col4\" class=\"data row6 col4\" >0.8966</td>\n",
       "                        <td id=\"T_95580_row6_col5\" class=\"data row6 col5\" >0.8378</td>\n",
       "                        <td id=\"T_95580_row6_col6\" class=\"data row6 col6\" >0.8391</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_95580_row7_col0\" class=\"data row7 col0\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row7_col1\" class=\"data row7 col1\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row7_col2\" class=\"data row7 col2\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row7_col3\" class=\"data row7 col3\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row7_col4\" class=\"data row7 col4\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row7_col5\" class=\"data row7 col5\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row7_col6\" class=\"data row7 col6\" >1.0000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_95580_row8_col0\" class=\"data row8 col0\" >0.9744</td>\n",
       "                        <td id=\"T_95580_row8_col1\" class=\"data row8 col1\" >0.9970</td>\n",
       "                        <td id=\"T_95580_row8_col2\" class=\"data row8 col2\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row8_col3\" class=\"data row8 col3\" >0.9286</td>\n",
       "                        <td id=\"T_95580_row8_col4\" class=\"data row8 col4\" >0.9630</td>\n",
       "                        <td id=\"T_95580_row8_col5\" class=\"data row8 col5\" >0.9434</td>\n",
       "                        <td id=\"T_95580_row8_col6\" class=\"data row8 col6\" >0.9449</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_95580_row9_col0\" class=\"data row9 col0\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row9_col1\" class=\"data row9 col1\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row9_col2\" class=\"data row9 col2\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row9_col3\" class=\"data row9 col3\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row9_col4\" class=\"data row9 col4\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row9_col5\" class=\"data row9 col5\" >1.0000</td>\n",
       "                        <td id=\"T_95580_row9_col6\" class=\"data row9 col6\" >1.0000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
       "                        <td id=\"T_95580_row10_col0\" class=\"data row10 col0\" >0.9724</td>\n",
       "                        <td id=\"T_95580_row10_col1\" class=\"data row10 col1\" >0.9967</td>\n",
       "                        <td id=\"T_95580_row10_col2\" class=\"data row10 col2\" >0.9500</td>\n",
       "                        <td id=\"T_95580_row10_col3\" class=\"data row10 col3\" >0.9729</td>\n",
       "                        <td id=\"T_95580_row10_col4\" class=\"data row10 col4\" >0.9594</td>\n",
       "                        <td id=\"T_95580_row10_col5\" class=\"data row10 col5\" >0.9386</td>\n",
       "                        <td id=\"T_95580_row10_col6\" class=\"data row10 col6\" >0.9408</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_95580_level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
       "                        <td id=\"T_95580_row11_col0\" class=\"data row11 col0\" >0.0261</td>\n",
       "                        <td id=\"T_95580_row11_col1\" class=\"data row11 col1\" >0.0049</td>\n",
       "                        <td id=\"T_95580_row11_col2\" class=\"data row11 col2\" >0.0643</td>\n",
       "                        <td id=\"T_95580_row11_col3\" class=\"data row11 col3\" >0.0447</td>\n",
       "                        <td id=\"T_95580_row11_col4\" class=\"data row11 col4\" >0.0381</td>\n",
       "                        <td id=\"T_95580_row11_col5\" class=\"data row11 col5\" >0.0579</td>\n",
       "                        <td id=\"T_95580_row11_col6\" class=\"data row11 col6\" >0.0562</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1a5fc2c5310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 25.6 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "model = create_model('catboost')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Tune hyperparameters**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_fa8ef_row10_col0,#T_fa8ef_row10_col1,#T_fa8ef_row10_col2,#T_fa8ef_row10_col3,#T_fa8ef_row10_col4,#T_fa8ef_row10_col5,#T_fa8ef_row10_col6{\n",
       "            background:  yellow;\n",
       "        }</style><table id=\"T_fa8ef_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Accuracy</th>        <th class=\"col_heading level0 col1\" >AUC</th>        <th class=\"col_heading level0 col2\" >Recall</th>        <th class=\"col_heading level0 col3\" >Prec.</th>        <th class=\"col_heading level0 col4\" >F1</th>        <th class=\"col_heading level0 col5\" >Kappa</th>        <th class=\"col_heading level0 col6\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_fa8ef_row0_col0\" class=\"data row0 col0\" >0.9750</td>\n",
       "                        <td id=\"T_fa8ef_row0_col1\" class=\"data row0 col1\" >0.9945</td>\n",
       "                        <td id=\"T_fa8ef_row0_col2\" class=\"data row0 col2\" >0.9286</td>\n",
       "                        <td id=\"T_fa8ef_row0_col3\" class=\"data row0 col3\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row0_col4\" class=\"data row0 col4\" >0.9630</td>\n",
       "                        <td id=\"T_fa8ef_row0_col5\" class=\"data row0 col5\" >0.9441</td>\n",
       "                        <td id=\"T_fa8ef_row0_col6\" class=\"data row0 col6\" >0.9456</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_fa8ef_row1_col0\" class=\"data row1 col0\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row1_col1\" class=\"data row1 col1\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row1_col2\" class=\"data row1 col2\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row1_col3\" class=\"data row1 col3\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row1_col4\" class=\"data row1 col4\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row1_col5\" class=\"data row1 col5\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row1_col6\" class=\"data row1 col6\" >1.0000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_fa8ef_row2_col0\" class=\"data row2 col0\" >0.9500</td>\n",
       "                        <td id=\"T_fa8ef_row2_col1\" class=\"data row2 col1\" >0.9973</td>\n",
       "                        <td id=\"T_fa8ef_row2_col2\" class=\"data row2 col2\" >0.9286</td>\n",
       "                        <td id=\"T_fa8ef_row2_col3\" class=\"data row2 col3\" >0.9286</td>\n",
       "                        <td id=\"T_fa8ef_row2_col4\" class=\"data row2 col4\" >0.9286</td>\n",
       "                        <td id=\"T_fa8ef_row2_col5\" class=\"data row2 col5\" >0.8901</td>\n",
       "                        <td id=\"T_fa8ef_row2_col6\" class=\"data row2 col6\" >0.8901</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_fa8ef_row3_col0\" class=\"data row3 col0\" >0.9000</td>\n",
       "                        <td id=\"T_fa8ef_row3_col1\" class=\"data row3 col1\" >0.9890</td>\n",
       "                        <td id=\"T_fa8ef_row3_col2\" class=\"data row3 col2\" >0.7143</td>\n",
       "                        <td id=\"T_fa8ef_row3_col3\" class=\"data row3 col3\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row3_col4\" class=\"data row3 col4\" >0.8333</td>\n",
       "                        <td id=\"T_fa8ef_row3_col5\" class=\"data row3 col5\" >0.7647</td>\n",
       "                        <td id=\"T_fa8ef_row3_col6\" class=\"data row3 col6\" >0.7868</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_fa8ef_row4_col0\" class=\"data row4 col0\" >0.9750</td>\n",
       "                        <td id=\"T_fa8ef_row4_col1\" class=\"data row4 col1\" >0.9780</td>\n",
       "                        <td id=\"T_fa8ef_row4_col2\" class=\"data row4 col2\" >0.9286</td>\n",
       "                        <td id=\"T_fa8ef_row4_col3\" class=\"data row4 col3\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row4_col4\" class=\"data row4 col4\" >0.9630</td>\n",
       "                        <td id=\"T_fa8ef_row4_col5\" class=\"data row4 col5\" >0.9441</td>\n",
       "                        <td id=\"T_fa8ef_row4_col6\" class=\"data row4 col6\" >0.9456</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_fa8ef_row5_col0\" class=\"data row5 col0\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row5_col1\" class=\"data row5 col1\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row5_col2\" class=\"data row5 col2\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row5_col3\" class=\"data row5 col3\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row5_col4\" class=\"data row5 col4\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row5_col5\" class=\"data row5 col5\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row5_col6\" class=\"data row5 col6\" >1.0000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_fa8ef_row6_col0\" class=\"data row6 col0\" >0.9000</td>\n",
       "                        <td id=\"T_fa8ef_row6_col1\" class=\"data row6 col1\" >0.9890</td>\n",
       "                        <td id=\"T_fa8ef_row6_col2\" class=\"data row6 col2\" >0.8571</td>\n",
       "                        <td id=\"T_fa8ef_row6_col3\" class=\"data row6 col3\" >0.8571</td>\n",
       "                        <td id=\"T_fa8ef_row6_col4\" class=\"data row6 col4\" >0.8571</td>\n",
       "                        <td id=\"T_fa8ef_row6_col5\" class=\"data row6 col5\" >0.7802</td>\n",
       "                        <td id=\"T_fa8ef_row6_col6\" class=\"data row6 col6\" >0.7802</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_fa8ef_row7_col0\" class=\"data row7 col0\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row7_col1\" class=\"data row7 col1\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row7_col2\" class=\"data row7 col2\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row7_col3\" class=\"data row7 col3\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row7_col4\" class=\"data row7 col4\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row7_col5\" class=\"data row7 col5\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row7_col6\" class=\"data row7 col6\" >1.0000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_fa8ef_row8_col0\" class=\"data row8 col0\" >0.9744</td>\n",
       "                        <td id=\"T_fa8ef_row8_col1\" class=\"data row8 col1\" >0.9970</td>\n",
       "                        <td id=\"T_fa8ef_row8_col2\" class=\"data row8 col2\" >0.9231</td>\n",
       "                        <td id=\"T_fa8ef_row8_col3\" class=\"data row8 col3\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row8_col4\" class=\"data row8 col4\" >0.9600</td>\n",
       "                        <td id=\"T_fa8ef_row8_col5\" class=\"data row8 col5\" >0.9412</td>\n",
       "                        <td id=\"T_fa8ef_row8_col6\" class=\"data row8 col6\" >0.9428</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_fa8ef_row9_col0\" class=\"data row9 col0\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row9_col1\" class=\"data row9 col1\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row9_col2\" class=\"data row9 col2\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row9_col3\" class=\"data row9 col3\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row9_col4\" class=\"data row9 col4\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row9_col5\" class=\"data row9 col5\" >1.0000</td>\n",
       "                        <td id=\"T_fa8ef_row9_col6\" class=\"data row9 col6\" >1.0000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
       "                        <td id=\"T_fa8ef_row10_col0\" class=\"data row10 col0\" >0.9674</td>\n",
       "                        <td id=\"T_fa8ef_row10_col1\" class=\"data row10 col1\" >0.9945</td>\n",
       "                        <td id=\"T_fa8ef_row10_col2\" class=\"data row10 col2\" >0.9280</td>\n",
       "                        <td id=\"T_fa8ef_row10_col3\" class=\"data row10 col3\" >0.9786</td>\n",
       "                        <td id=\"T_fa8ef_row10_col4\" class=\"data row10 col4\" >0.9505</td>\n",
       "                        <td id=\"T_fa8ef_row10_col5\" class=\"data row10 col5\" >0.9264</td>\n",
       "                        <td id=\"T_fa8ef_row10_col6\" class=\"data row10 col6\" >0.9291</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fa8ef_level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
       "                        <td id=\"T_fa8ef_row11_col0\" class=\"data row11 col0\" >0.0372</td>\n",
       "                        <td id=\"T_fa8ef_row11_col1\" class=\"data row11 col1\" >0.0068</td>\n",
       "                        <td id=\"T_fa8ef_row11_col2\" class=\"data row11 col2\" >0.0845</td>\n",
       "                        <td id=\"T_fa8ef_row11_col3\" class=\"data row11 col3\" >0.0457</td>\n",
       "                        <td id=\"T_fa8ef_row11_col4\" class=\"data row11 col4\" >0.0576</td>\n",
       "                        <td id=\"T_fa8ef_row11_col5\" class=\"data row11 col5\" >0.0845</td>\n",
       "                        <td id=\"T_fa8ef_row11_col6\" class=\"data row11 col6\" >0.0805</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1a5fc26f640>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 33 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "tuned_model = tune_model(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_model(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_model(model, plot = 'confusion_matrix')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VbR7LVmr3t7392QFTy50tdiJ5cJrUBUGwJHQACA8PR0gIh+LdxZapHX6+1r1t8lZqMjcrP12BSdcPszqWmNINX3x/hEmdSCacZueMjAzce++9mDVrFgDg448/xvXXX+/zwJRGLi1TClzcn51I/pwm9ccffxybNm3Cxx9/DEEQkJGRgZycHDFiUx4/b5lSYOP+7ETy5zSpr1ixAjfeeCPmzp2LsLAA7CIWga681PLvgO2KJ7/A/dmJ5M1pUh8+fDg+++wzPPPMMxg4cCDGjRuHrKwsJCQkOPtVclFFUyhUhvDA64rnWnev88ZyNO7PTiRfQc7uMHXqVDz33HPYtWsXxo4di7Vr1yIzM1OM2AJHTLypW77teLuCxfRXI61bLNJC9dY/ClrrXri7CJve/hcKdxeJ8nwb121HTIIKk3KHISZBZelKJ6LA4bSl/s477+DAgQMoLS1Feno6/vKXvyAjI0OM2JTHUcs0ACl1Db+Z2Ou9uRyNiAAXkvqXX36JixcvYvr06cjIyMB1112HiIgIMWJTlNZV2HTlpahoCgVi4k0nk66VNDbyLikSLJejERHgQvf7hx9+iJ07d2LkyJH47rvvMGfOHMyfP1+M2BTB2NSI2pLDNmvUVUkDEdR3iOmH6/79znhhu8dd5+WnK6yWhQGmBHvu1HkvRWfLvBytNS5HIwo8TpN6fX09Dhw4gH379qGwsBCxsbEcU3eDeX16qSHc8lPRFGrqir900eonULvi/U34gbUdGpuWIsGOGT8UR/aesjzvV9sP44vNB3z2fETkn1SCINgM8wJAaWkp0tLScMMNN2D06NEYO3YsMjMzER8fL3aMDun1emg0Gjy+vwo1+mapw7GrtuQwSg3hVuvTjU1NwLH/IDHEgKjeaVb3t7ekjdXoxFN/9GvkZl6yKcCirRLc6sY2j6mLvd67cHcRDhX+gBtnDrV5bm7UQiR/k9IXQaPRQK1WIzw83Oa8w37fpUuXYseOHfj2228RHBzslWAMBgMee+wxVFRUoLGxEYsXL8aECRMs5zds2IBt27ZZLhyeeeYZ9Otnu3e03AWFhEBIGoioUL1Lk8Xaq0bXq3yH5cLA1wk+EC4uIrUnkZgy0OqYJ2PTvlzv3V5yFgTBktDNsQPAS0+8i0k5I7hRC5HCOUzq5ga8txI6YNocpnPnznjxxRdx6dIlzJo1yyqpFxcX4/nnn4daLe8lTa2Tn668FEJTKARz13rStZ6NoTuoRlehrfHZGve2SVxXXoqK2nogKg7okQqV+XUoaH19fewAr5VK9cV6b2ez6h1NmIuNj+DMeKIA4DC7XLx4EY8++qjDX1y9erXbTzZ58mTcfPPNltttLxiKi4vx1ltvoaqqCjfeeCPuuOMOt5/DH9SWFOFkSbEp+SHUdFBbA+hqAWMT0M+Lye/qGndflJu16SHooYaqB0zzAXSXoOo7BICySt1Gpmdi1861mDzF/0qlujKr3n799iqkpFtfEHJmPJEyOUzqkZGRGDVqlFefLCoqCgBQV1eH++67Dw888IDV+alTpyIvLw/R0dG45557sGfPHowbN86rMYih4WIZVD1S7HaXC2U/QujSUz6V0xzVq29nUp/cu+n1I++Dtmq7KKVS3RnndmXZmr367YU7j2LMlMFWv8eZ8UTK5DCpd+7c2bIzmzddvHgRd999N/Ly8jB9+nTLcUEQcOuttyImJgYAkJWVhaNHj8oyqQNwmAzjg5vRLVQPKKhyWltK2JHOnCTNy9B80aJ1t0CNq7uotR3PX7w0jxu1EAUIh0k9NDTU609WXV2N22+/HcuXL8fo0aOtztXV1WHatGn497//jcjISOzfvx9z5szxegyu8GVLMyKhl2dJTW7V6GS+I52vK8J5UqDGnV3U2o7nc6MWosDgMKlv2bLF60/2xhtv4MqVK3j99dfx+uuvAwCys7PR0NCAnJwcPPjgg1iwYAHCwsIwevRoZGVleT0GV/hbS9OmGp15shoA9EhtWeMuZne+tsb0vIB8hhJcNM74EWJ9XBHO0wpwHUnO3KiFSPlELWX2xBNP4IknnnB4fubMmZg5c6YosbTXGjc2G/yqpdm6TnpMfzWirOJuNv34qjvfQQ9BYogBUaFX/xYKG0oQo+Sqq13p9jA5E5EjAVuftN213w2VQA/Pk1REr77AJfvJMKJXX48fFxB3I5TWPQRWusUipv8Nfj/hzVMdSbiucqcrnYjIVS4l9UOHDuHEiROYM2cOfvjhB4wcOdLXcYnDUWu8obJjDztwGNJOOkqG8mnRdugCwgd7pdcf24vIKydQHzsAkem+K1UsVsLlODcReZvTpL5x40Z8+eWX+OWXXzB58mQsX74cc+fORUFBgRjxyZLStxV1pv0WvmcXNeEH1mLGlN5ITBmIirJq7Nq5FvqR93U8WAfESrjsSicib3Ka1Hfs2IEtW7Zg3rx56NKlC7Zt24bs7GzlJ3UftDQDhbcvauqPfn01obdMXJs8Bdj07V6ft9iZcIlITpwm9aCgIISFtYydhoeHe7V0rD+K6JmCtJAQiNF93nrCnrHZgIYLZ6ziMJeUlUPRFl9xVI898rPjALhjIBGRmdOkPmrUKDz//PNoaGjAl19+ic2bNyMjI0OM2HzPQWs8qFusaN3n1hP2wlsm6NVWQSg/D1XSQFkUbfHl2n5H9djrYwcg0uNHJSJSHqdJfenSpdiyZQsGDhyIjz/+GFlZWZg/f74YsflU23FfY1MTGi6Wmf7dHIHaksNW9/VpK9nh8jn4rK67t/lybb+9euy7dpYjcqT3Kx4SEcmZ06S+cOFCvPvuu4pI5K21HfetLTmMCxHdTUnJCNMPIItWst/w4dp+/cj7TGPonx03tdCZ0ImIbDhN6g0NDbh48SJ69uzp7K7y50cFZ8iWaVJcple73J8cd9qLj0ZEJC2nSb2mpgbjx49H165dER4eDkEQoFKp8NVXX4kRH5HXiLXOnYhIKk6T+rvvvitGHIHN0fI5c311kZbSyX3L1PaIvc6dfMudLWuJAonTpH7gwAG7xxMTE70eTCBqPWHPZklb7xQEhYi3TWuHJ7v56dr+9ta5Yxz3FJcbX++gRyRnTpP6/v37Lf82GAw4dOgQRowYIdrGK6LyclJypeXbdsJel8HXe/Rc7jxnuzycV+CNKnK+6ilof507k7qceLJlrRKxp4IccZrUV69ebXX78uXLePDBB30WkFR8UdpUii1cpdo21htV5HwVe3vr3L2BX7DiEWMHPX/Hngpqj9u7tEVGRqKiosIXsUjKZ/XapZhRL+dZ/F6K3WpW+7gkbFz3XwDWG7Ssvvt3HYsV/IIVmxg76Pkz9lSQM06Ten5+PlQqFQBAEAScP38emZnynTnsz5PB/Dk2f+XqkjRfbNDCL1jxBfqWteypIGecJvV7773X8m+VSoUuXbqgf//+Pg3Kl6Tqnm7L2NRkVbUOAHTlpaiorQdSh0MV0uqtETM2P5vsZmxqAs4fhy7EAADI+91Fyzn1iDS409nk7Q1apP6CDdRu/0DesjbQeyrIOaffiJ9//jmefPJJq2OPPPIInn/+eZ8F5XN+0D3dcLGspYKdWQ81VBFVEHSXoOo7RPTYfDGvoMPOH4UqJh4X4hIAA/DMwb6m47VVeAqlGH5DujRxQdov2EDv9g/UHfQCvaeCnHOY1B9//HGUl5dDo9GgtLTUcrypqQlarVaU4BTBQcu3oeoC8P/U9i8uaqt88pzOWtt+sQ9829i1NUDSQAcXYTrx4rJDqi9YdvsHtkDuqSDnHCb1xYsXo6KiAitXrsQ999xjOR4cHIzU1FRRgpO71i1f7ZnjuFh+BugUBQCoEVRQufAYbbuf2z5+23F2v2xtu8he7LoQAy5IF5JT3viCdbcbXepuf5JeoPZUkHMOk3pSUhKSkpLwySef4PLly2hoaIAgCGhubsaxY8cwevRoMeOUpdYtX115KVTpoy3d7cL54649SJvuZws74+yuTrTz1wl5DnsKbK9n/EpHvmA96UbnuCoROeJ0TP3VV1/F3//+dzQ1NaFz58745ZdfoFarsXXrVjHi8w2pJoO1GssX2utiN5eHvfpvx93P1q1xVycBSjFZkHXXbXnajc5xVSJyxGlS37FjB7755husXLkSixcvxunTp/HBBx+IEZtPiNE9ba8l3FB1AUJTKISYBASZZ7Y7uLhIDDEgKtQUn9vdzy5MAjQ2Gxzez9hc586zucRR3XWXE72jizCZ60g3OsdVicgep0n9mmuuQXR0NNLS0lBSUoJJkyZhzZo1YsTmNWJ3N9ttCf+/SVDVVkE4fxToOwRIutb07/PHEX/pLLoNzzLdr1ssYvrf0NJV3mxo2du9DWOzZ/3SDRfOAD3sX8A0XDjT4VK1rTmqu771/55C7oKhTjdYaX0R1no5G2Be0iZfHe1G57gqEbXlNKlHR0fj448/xuDBg/H+++/jmmuuwW+//SZGbF4jydp0Ry3m4/815egerpUobS8B1/ywD0HBoZbbuvJSCN0GuTQBTyyO6q737hlqd4OVti321uPsw29Q1t7n7EYnIm9zmtRXrlyJzz77DDNnzsSePXuwfPlyPPDAAyKE5mVeXJveXss/qu8A6MpLHSZiRMVBBUD4bhtUKUOApIG4lDQQl8yN7lYXGsamRtPSt4judrufa7r0wSVDeMuxiO7Az6eAhN5uvyZfsV93vQop6dbvRcsGK4E13u5qN3qgFpohIvc4Terdu3fH/PnzUVJSgqVLl+K3335DZGSkGLH5rfZa/lF7nkNdQipUPRz8ckw8EJeA+OBmXHJwoaErN10w6MpLURMSC9RWmybMVZ8HImKABi3QLQlI/71V5TkBAH4ua5lk1youm0mAIo1TR6ZnYtfOtZg8xdwarcK/t/6EP2QPsbqfeYOVQPxkOetGD/RCM0TkOqdJ/bvvvsPy5cvR3NyMzZs3Y/r06XjppZfw+9//Xoz4/Ebr1rmuvBRCU0u3N5KuRVBICAQAdSFRQFSc08eLSOiFSw7OVTSFQmUIb6kwByCo7xAYz/wIVVwChNoqqOISrEvJXpUYF2mZZGfRZhJgRM8UCOXnbZ9YW4OI3ilOY3eVeSLcpdih2Pp/X6F3z1CkpPfEH7KH4IuPijBpzlBLt/OuneWIHDnL6vddreuuZCw0Q0TucJrUX375ZXzwwQdYuHAhEhIS8P777+Ohhx7yy6TuqFvcnbHm9h6jIryrqWXdQ93yWK0nvwGW4jIdagnHxLcsfXPn9wBE9U5zOkcgKCQEqqs9BvbOeUPbGe/f/RaKOYuyLOcnzRmK/9tSg7ioX00t9DYJPdCZu9trfr2C+fdkWZ1TeqEZDjUQec7pN7jRaERCQsuXf0c2czEajXj66adx/PhxhIWFYcWKFejTp4/l/O7du7Fu3TqEhIRgzpw5mDdvnluP77BbPKI7cOowhLYJq023tLGpET/v2WFbk938GNoaqPpZJ0y7SbdHKgTdJevj2hpAVwuMmApopV2O5etlffZmvI+eOBiHvz2B4WMHWI7FRf0KXP8XS5c7W+Ymrbvbv9p+GBVlVUhMafk8KrnQDIcaiDrGaVLv0aMH9uzZA5VKhStXruAf//gHevXq5dGTffnll2hsbMTmzZtRVFSE5557DuvXrwcAGAwGrF69Gtu2bUNERARyc3Mxbtw4qwsKlzgYp05sqHTaLa09qUFFbT1UPRxMqtPWuBSCKiTEakMWABAuXYRw/jhU2qqWZN+R1nwHCuj4usa7oxnvRYWlwFjT7dZj6O0l80BrtbXtbp8wezi2vfUNRk8crPgZ8nIZagi0zyTJi9Ok/re//Q0rV67ExYsXMXHiRFx//fX429/+5tGTHTp0CGPHmr7Vhw4dCo2mpZv71KlTSE5ORlycaTz6uuuuw8GDBzFlyhSPnqstV7qlTXd0Ph5uw1wBzkmythSV6RaLqL4jEHXmBMytZV15KSqaQk0T6ZKutf/45ouKqC4Qfj7VcltXaxpL751m09J2d42+N9b0O5rx3iky/Oq/W8bQ20vogdhqs1eQZu6iLLz30pfonthV0YVm5FDTPhA/kyQvDpN6ZWUlunfvjq5du+Lll1/2ypPV1dUhOjracjs4OBhNTU0ICQlBXV0dYmJiLOeioqJQV+f96mY+UX2+JYn3HgDh2HdI7NsPUb1bFUdpU1QGgM1Fhso8dKBtdVHQ6mLA2DsJDRfLgIZKRCT3tVqj7ijhurtG3xtr+m1nvFdj187zuBQ9DMdfO+7SGLpcWm3e5qggzcjM3yn6dQP+X9M+UD+TJC8Ok/qdd96JHTt2AAD+93//F7fffnuHnyw6Oho6Xct2mUajESFXx7nbntPpdFZJvj3aUxrU1jWYdjRDuNP7e0xXa3e5WHxwMyLMu6gZahExegLiBg11q1Jd++PcLRcDXdSj7LamzbftJnc31ug3XShGf+Ov+DloIHTJ1zu9vyP6kfeZisl81pLETWPnmS6Nocuh1eYLgVyQxt9fe6B+JkleHCZ1QWjpQP7000+9ktSHDx+OPXv24A9/+AOKioowYEBLVbXU1FScPXsWly9fRmRkJA4ePIiCggKXHvdMUxguVleiV0Olw0Itbm3W4qj73NFysYy7PSo162lXt68q5IUfWIvb5/VGYkpfVJRV4+NPNuJw8q0ePRaAq9XhMj1ae+7vrTZfCuS67v782gP5M0ny4TCpq1QtC8BaJ/iOmDhxIgoLCzF//nwIgoBVq1bh008/RX19PXJycrBs2TIUFBRAEATMmTMH3bt3d+lxVXHXANrfENElAmnBoejQrO6oWAjaGutJcVfHrHuMm+U0ebuTqDuUnL1YIQ+wP2N95h+B45/st2qxu8vcGn92Tz+bY+3x91abrwVyXXd/fe2B/pkkeXBpUXLrBN8RQUFBNpPsUlNTLf8eP348xo8f7/njB4d2aFZ3TH81BkADIN7uOQCoLTkMwLSZSsOFM5bzET1TEBQSAu3ZY7iobbSdcKerRT99A0LCI1oOXS0n683k7ClHM9Z7NGpwCrZJvb2Ll1UF0QgLs/5oebJczZ9bbRSY+Jkkf+cwqZeWlmLChAkATJPmzP8WBAEqlQpfffWVOBGKyNlSr9qSw61a1uEt9d1rqyCUn4cqaSCEc+egSh9tt/V9ufi/uJQ8zHJOaAoVZ/MVB8MJxs6RlouUJl243a7Fi01dWmb2txrCaK+XQXPwIobfkO6V0P211UaBi59J8mcOk/rnn38uZhyScXtc22G3N6Dq0hNCp6h279P6nCDCnuDtTcAzNhtaEnPCcHy849+YOatVjfaPT6JX0k2m37U3hOHwdepARETic5jUExMTxYyjQ4TaX9yfDHeVJNuyeoOLxWfa632oLTkMxEVbEvPhLgU4/sl+9Kg/iOagbug6fik8WLVPXsACJ0TkCe8U+pZY35BGRHekxKkLk86MTY3tb6nqKQ8qw/myzKsu+XqcvJSMtLaz/Ek0LHDiX3iBRXKiiKQek6qGQd/s0+doKSHr4A7GJhjP/GjaJtVVSdeaNoM5fxyoPo/EHt1NBWucJGdvlnkVmpognPnR+qC2BroQg8sV5Mh77Bc4EVjgRCK8wCK5UURSNxef6UgSMjY1AeePtnpQU2IDWma+IyrOccv67FGoUoZASB3q8D7h8T2szqmAlklzAKJ69xW/u//nU7Y7tsUl4EJtFaJOOhl+EGlP9kBiv8BJAv73w51M6iJjBTmSI0UkdUvxmfIdLq0lt+v8Uaski7gEXACA6qqrXd2w3n2t2QhUnQUatIgPbkZ4Qg/8HJfQ0vo2JzdtjanMa+80RI0YgaBvP0PFz2VARBRQ83PL83eKhK685SJCtBayrhZIGuj2sjrzEEDe787YnFOPSLP9BXKJowInfQZ2ZzIRGSvIkRwpIqmbi89U/FzmvHVpT22VqdiMg+RmbK5DUHCo7e5rqUMhXLqIblfHn382XN2PvNV9hEsXERWqt8TUY9wsRJ3UQFdeigspQ6xayK0vInzVYm8929/Y1IT4xsu45MHjmIcAht/A7VK9acz4oVj77EbcOHOopcDJwa9LMOO23+OLTUwmYmIFOZIjRSR1Cw92WDO3OKvPHcGlpIF279Nw4Yz15iwdEBQShlChDgnB51H7m4D6tlu0AvBV4RnzfvEVtfUtf6vmYHHWygeYjkyuum7M71By5ByKCkvRs09XzLjt90wmEnBUQa5/ej9sevtfnDhHfilI6gCkZm5xRiS4sEd8bZVpX/RWP+6OIYcfWIvcsb/i/kdGYdn8cAw/t9HDyN2nPanBhYjuUA0cBVXSQKiSBgLdmCi8beO67YhJUGFS7jDEJKgsicFVY8YPRYPWgKFj0jB87ABLMmECEd+td8+GtkrAF5uOQFtluuTuyHtL5GvKaqn7kLNlZNqTGqfL03xVX90tbZbvCbVVHi2rI/u8NbmK5Uj9h7mCHCfOkRwoIqlbis90VDuzuZ0tI2ub9M214Y3GZmh1FdCVlyK+8QQSb73R6vfaq68uiqRrIRz7D1D2Y8uSOsAra94DkTcnV8mpHGkgrOXmxDmSA2Uk9YunIWi1QJTnLcuInikQys/bntDWIKJ3itPfb5v0a0sO40JEd6uJcLWVQvv11QHRW8hBISEQkgZKt6ROxuwlskCcXCXmWm4pLx4C8b0l+VHEmHpK7yQMSOmLAdfEe9y6DAoJgSomHqq4BOufmHjTjHZPXO3qNv/UD5qEj3ecREWZqUCNqb56KXolDUBaqN70I1ULWVfr9q94svOaJwp3F2HT2/9C4e4iUZ7PFY7GzceMH4oje0+1eo+tx8P98bV0hL0u6WGZqT55fR2dq9BRzt5bIn+gEry1WboE9Ho9NBoNHt9fhZoOVpRze2MXJ2pLDqPUEG67RO7SRUSW7UOvyLqr9dXzfR6LVUwO6tz3aqh0e42/GEnd3Ar0p/2r//PVEcReE2TTYtNWCVbJu22L0h9fiyOutog3vf0vTModZnP8i01HkLtwmtficeVvLpZAGGog/zUpfRE0Gg3UajXCw8Ntziui+90bvFl61RldYwhKe4/HgAj7FyK+2mSm/cl+N/hdSVh/nZjkythq2/Fwf30t9rjTnS5Wl7Q/jWfLaa4DBR4mdQd81Vq2+PkUkNLX8XkXNpkB3ItTzAsXb/CnL/LWPElkYr8WT1uT7l58OFrL7e0eCI5nE7lGEWPqrjA2NaK25LDdH2NTo839za3lUkO49U/1FWhPalx7PEfr2qPiPBrDtsdZnL4iRte7+Yu8NX/4IvdkbFXM12I99gysf+EDl3+3/HSFVeIETMn63Ck7k0ivaruW2xdDChzPJnJNwCR1j5Jfm4luqi49LV3izh4vpr8avRoqIZw/DqG2quUHAHqkIjEu0nsT4tqJ0xfEmiDnz1/k7iYyb76W9ibb2ba0EzBmyrV46Yl3XXpsTy8+xowfityF03z63ohx8UAkdwGT1AF4P/m183hBIWGI6p0GVdJABPUdYvWjCglBVO80vxvD9jVPZn778xe5u4nMG6/F2Qxw+y3tBMTGR7j0d/fnCylAnIsHIjkLrKTuAnO3uq68VNpAvFCS1p90ZDmSkr7IO/JaXFk+ZmppW39OKsqqkZLes90u9Nb8+UKKiNrHiXJtmLvVhaZQ72x04kEJVmclaT1Rf2wvIq+cQH3sAESmZ3r0GJ6S08xvZ6RczuTqrPv1L3yAMVMGW+3yNuLGQYgM7+Lyc3GGN5E8ManbY+6S72BNdE+Ts9uz1J3EGX5g7dWa8wNRUVaNXTvXQj/yPtcfv4Ncnfnt7+t/2y71Wv/CB+jcJVa0eF2dAb54aR5eeuJdxMZHICW9J0bcOMiv18QTkfcEVlJ3J0knXQvh/FHT+WYjcE6D+OBmRCT0grEpEg0Xy4CI7u0+nhhLyJxdONjbRGbyFGDTt3sdtti9PRHOlWQkZqlRT9jrbRgz5VpUnr9kGU7wdbzuLB/764oCy0VSZHgXv/pbEpHvBExSd7fVHBQSAlzd69x45keoUobgUlwCLgGAAAjdBgGnDiOxodJ6r3U3usi90SXu7MIhUnsSiSmmfeIPf3sCF8/VoGdyPCKv/ArA9jl9MbPdWTKSQ/e8/d6GBBQVnsTwsQMAWMfrrNfB014Jd3ZvYxc6UeAJmIly5uRn78elWehtZroHJfSGauAoRPVO8+jxzPuq33XPQOSO/RXhB9Z64VXaqo817cf9zw3/QfekeEz9Uwa6J8UjvFHcSXftTb7yZG202Bwt9erZpysA63idTQp0Z9KgvRUDSpo4SETeFTBJvT2tC8noykshHP8vjD99bfqpKge0NV59vvqjX2OyTZd4b9Qf2+vV5wGAyPRMbP2/Ioy4cZD1880a5JPna4+jZOSvRWZas13qVYWDX5dYWunmeJ3NUHdnAxRvbmAi1UYyStvAhsjfManDupDMhR5qqAaOgippIFQx8UisLkFiiMGrz2fqErdtmUZeOeHV5zEL69pb1Odzl7+vjTZr3dvwxeZDGHHjIADW8TrrdXC1V6Iju5+1TaRS7W4m9a5qRIGISd3MQSGZqN5p1mPmXmDuEm+toqwa9bEDvPo8Uj2fJxx1z/tbS8/c2/DXFQV247Xf61CFirOV7Zy37ZXwdEiibSJ98fF327048NXfV8wtWYmohahJXavV4s4778Qtt9yCnJwcHDlyxOY+K1aswOzZs5Gfn4/8/HxotVoxQ3TMi8VgItMzsWtnuVXLdNfOcp+tH3f1+cQq/+pI2+55f2/p2RtOGDN+KAp3Flv9rQ9+fRyTckZYJtK50ivhyZCEvUQa1y3C4cWBL/++3p4n4W8Xd0T+StTZ7xs2bEBGRgb+/Oc/4/Tp03j44YexY8cOq/sUFxfjnXfeQXx8vJihtcsXxWD0I+8zLSv77Lhp9vvIWR0P1I+er6PkMCPekc5dYlF5vgZFhaXo2acrZtz2ewCwrMt3ZQa7J7uf2ZuhnzKoJyrKqpCY0lIOuaKsGga9EcOyfPf39eauav6+3JHIn4ia1P/85z8jLMw0M7y5udlmg3ej0YizZ89i+fLlqK6uxty5czF37lwxQ7TLPHPe3jan5tv2tmN1ti2qqaWciUifRG1L7OfrCH/ddtUVhkYjuifFWybRAaYu+KZGo+W2K8vN3Fm+BthPpN2T4lG4s9iqwtyRvacQFh5mtyXtrb+vt7ZklfPFHZEUfJbUt27dio0bN1odW7VqFYYMGYKqqiosWbIEjz32mNX5+vp63HLLLbjtttvQ3NyMBQsWQK1WY9CgQV6Ly16i1ZWXQqith5A6HKqQVn+SNoVpzBPqbDaBqa1CGjQ268XdvT+1cLWl549V6ELDgnDw6xIAg1qVaj2OiE5Rbj+WO2vNHSXSxUvzbC4OCncXdagl7crf3d2LEnvkfHFHJAWfJfXs7GxkZ2fbHD9+/DgeeughLF26FKNGjbI6FxERgQULFiAiIgIAkJGRgZKSEq8mdbuJtocaqogq9KoucV5I5uqEutZMVeXadM17en8C4FpLz1+7ZZNTkxCToLLqgh9x4yBoq2zqD3qkvYRqTqQffvYNDL8ZMDLzdwBsLw460pJ25+/e0QI43uzGJwoEok6UO3nyJO6//36sWbMGWVlZNufPnDmDvLw8NDc3w2Aw4PDhwxg8eLD3A2lnprtHhWnIJ9orWOPPs6vNk+G6J8Vj6i2j0T0p3mtL9FyZ3Hby2GmMnToY+X+9qd0JcJ7sxib2310uyx2J/IWoSX3NmjVobGzEypUrkZ+fj8WLFwMwTaD76quvkJqaiunTp2PevHnIz8/HjBkzkJbm3eVkZJ/UM98dcVSwxt+r0Pli+1JXEqq7Sdfd6nRS/N25FSyR60SdKLd+/Xq7x2+77TbLvxcuXIiFCxeKFRJd9eyefn6b2O2RQ7est2uvuzK+7OsxaKn+7qxjT+QaFp9xl7vr1b24vp1aBGK3rCtr131dcjcQ/+5EchKYSd3DRBvTX420brFIC9Vb/zhYr+7u/aUkp1a6WaB1y7qSUMVIuoH2dyeSE5UgCN6ZkisBvV4PjUaDx/dXoUbf7NLvmJe0GZuaTHuitxLRqy+CgkPtrjlXIjkmcnJtOZk/LvUjoo6blL4IGo0GarXaptYLEED7qZuZC8nUlhzGhYju1kvbjAAucQ05eYevEqsr48scgyYKTAGX1K0E4Bpyts7F4Q9r6NlaJwo8gTmmTuRD/rCG3t83wyEi32BSJ/IyqdfQ+8NFBRFJg0k9wDy7p5/UISier5eVOSP1RQURSSewkzrXkJMPSL2WW+qLCiKSTsAmdTmtISf5kXItt9QXFUQknYBbp04tOBNe2Tj7nUh5uE6dHJJbvXdyD9eqEwWegO1+J5Nn9/Tj5DkiIoVgUiciIlIIJnUiIiKFYFInIiJSCE6Uo4DF2eFEpDRsqVNAYm10IlIiJnUKOKyNTkRKxaROAYe10YlIqZjUKeCwNjrJVeHuImx6+1/sVSKHmNRJVrzxpcba6CRHnAdCrmBSJ9nw5pealBuuELmL80DIVUzqJAu++FIbM34ochdOYwud/B7ngZCrmNRJFvilRoGM80DIVUzqJAv8UqNAxnkg5ComdZIFfqlRoOM8EHIFy8SSbNx692wU7i7CF98fQXJqEr/UKOCMGT+UF7LULiZ1khV+qREROSZqUhcEAZmZmejbty8AYOjQoXj44Yet7rNlyxZ8+OGHCAkJweLFizFu3DgxQyQiIpItUZP6uXPnMHjwYLzxxht2z1dVVeG9997DRx99BL1ej7y8PIwZMwZhYWFihklERCRLok6UKy4uRmVlJfLz87Fw4UKcPn3a6vyPP/6IYcOGISwsDDExMUhOTkZJSYmYIRIREcmWz1rqW7duxcaNG62OLV++HIsWLcKUKVNw8OBBLFmyBB999JHlfF1dHWJiYiy3o6KiUFdX56sQiYiIFMVnST07OxvZ2dlWxxoaGhAcHAwAGDFiBCorKyEIAlQqFQAgOjoaOp3Ocn+dTmeV5ImIiMgxUbvfX3vtNUvrvaSkBL169bIkdAAYMmQIDh06BL1eD61Wi1OnTmHAgAFihkhERCRbok6UW7RoEZYsWYJvvvkGwcHBWL16NQBgw4YNSE5OxoQJE5Cfn4+8vDwIgoAHH3wQ4eHhYoZIREQkWypBEASpg/CUXq+HRqPB4/urUKNvljocWXty3GnndyKvK9xdhHOnziM5NYnr74nIqUnpi6DRaKBWq+02elkmlkgi3B+biLyNSZ1IAtwfm4h8gUmdSALcSpaIfIFJnUgC3EqWiHyBSZ1IAtxKtn2Fu4uw6e1/cTiCyE1M6kQS4f7Y9nECIZHnuPUqkYS4law1exMIAVPLnX8nIufYUiciv8EJhEQdw6RORH6DEwiJOoZJnYj8BicQEnUMkzoR+RVOICTyHCfKEZHf4QRCIs+wpU5ERKQQTOpEREQKwaRORESkEEzqRERECsGkTkREpBBM6kRERArBpE5ERKQQTOpEREQKwaRORESkEEzqRERECsGkTkREpBBM6kRERArBpE5ERKQQTOpEREQKwaRORESkEEzqRERECsGkTkREpBAhYj7ZW2+9hW+//RYAcOXKFVRXV6OwsNDqPitWrMDhw4cRFRUFAHj99dcRExMjZphERESyJGpSX7RoERYtWgQAuOOOO/DXv/7V5j7FxcV45513EB8fL2ZoREREsidJ9/sXX3yB2NhYjB071uq40WjE2bNnsXz5csyfPx/btm2TIjwiIiJZ8llLfevWrdi4caPVsVWrVmHIkCF488038fLLL9v8Tn19PW655RbcdtttaG5uxoIFC6BWqzFo0CBfhUlERKQYPkvq2dnZyM7Otjl+8uRJxMbGok+fPjbnIiIisGDBAkRERAAAMjIyUFJSwqRORETkAtG73/ft24fMzEy7586cOYO8vDw0NzfDYDDg8OHDGDx4sMgREhERyZOoE+UAoKysDGPGjLE6tmHDBiQnJ2PChAmYPn065s2bh9DQUMyYMQNpaWlih0hERCRLKkEQBKmD8JRer4dGo8Hj+6tQo2+WOhxZe3LcaalDICIiJyalL4JGo4FarUZ4eLjNeRafISIiUggmdSIiIoVgUiciIlIIJnUiIiKFYFInIiJSCCZ1IiIihWBSJyIiUggmdSIiIoUQvaKcN5nr5nQO47VJRwULtkUMiIjIvzQ2NgJoyX9tybqinFarxYkTJ6QOg4iISFQDBgxATEyMzXFZJ3Wj0QidTofQ0FCoVCqpwyEiIvIpQRBgMBgQFRWFoCDbXmpZJ3UiIiJqwcFoIiIihWBSJyIiUggmdSIiIoVgUiciIlII2a1TFwQBmZmZ6Nu3LwBg6NChePjhh63us2XLFnz44YcICQnB4sWLMW7cOAkidZ1Wq8WSJUtQV1cHg8GAZcuWYdiwYVb3WbFiBQ4fPoyoqCgAwOuvv253OYPUjEYjnn76aRw/fhxhYWFYsWIF+vTpYzm/e/durFu3DiEhIZgzZw7mzZsnYbSuMRgMeOyxx1BRUYHGxkYsXrwYEyZMsJzfsGEDtm3bhvj4eADAM888g379+kkVrltmzpxp+RwlJSVh9erVlnNyfK+2b9+OHTt2AAD0ej2OHTuGwsJCxMbGApDfe/XDDz/gpZdewnvvvYezZ89i2bJlUKlUSEtLw1NPPWU1+9nZ/3v+ovVrOnbsGJ599lkEBwcjLCwMzz//PLp162Z1//Y+o/6i9WsqLi7GnXfeaclRubm5+MMf/mC5r8/fJ0Fmzpw5I9xxxx0Oz//yyy/CtGnTBL1eL1y5csXyb3/2yiuvCBs2bBAEQRBOnTolzJw50+Y+8+fPF3799VeRI3Pf559/LjzyyCOCIAjCkSNHhDvvvNNyrrGxUbjpppuEy5cvC3q9Xpg9e7bwyy+/SBWqy7Zt2yasWLFCEARBqKmpEbKysqzOP/zww8JPP/0kQWQd89tvvwkzZsywe06u71VrTz/9tPDhhx9aHZPTe/XWW28J06ZNE7KzswVBEIQ77rhD+P777wVBEIQnn3xS+OKLL6zu397/e/6i7Wv605/+JBw9elQQBEHYtGmTsGrVKqv7t/cZ9RdtX9OWLVuEd9991+H9ff0+ya77vbi4GJWVlcjPz8fChQtx+vRpq/M//vgjhg0bhrCwMMTExCA5ORklJSUSReuaP//5z5g/fz4AoLm5GeHh1tXdjEYjzp49i+XLl2P+/PnYtm2bFGG65NChQxg7diwAUy+KRqOxnDt16hSSk5MRFxeHsLAwXHfddTh48KBUobps8uTJuP/++y23g4ODrc4XFxfjrbfeQm5uLt58802xw/NYSUkJGhoacPvtt2PBggUoKiqynJPre2X2008/4eTJk8jJybE6Lqf3Kjk5Ga+++qrldnFxMUaNGgUAyMzMxL59+6zu397/e/6i7Wt6+eWXkZ6eDsD+d197n1F/0fY1aTQafP311/jTn/6Exx57DHV1dVb39/X75Nfd71u3bsXGjRutji1fvhyLFi3ClClTcPDgQSxZsgQfffSR5XxdXZ1Vt3RUVJTNH1VK9l7TqlWrMGTIEFRVVWHJkiV47LHHrM7X19fjlltuwW233Ybm5mYsWLAAarUagwYNEjN0l9TV1SE6OtpyOzg4GE1NTQgJCfH798YR85BHXV0d7rvvPjzwwANW56dOnYq8vDxER0fjnnvuwZ49e/x+yAcAOnXqhIKCAmRnZ+PMmTNYuHAhdu3aJev3yuzNN9/E3XffbXNcTu/VzTffjPPnz1tuC4JgKbIVFRUFrVZrdf/2/t/zF21f0zXXXAMAOHz4MN5//3384x//sLp/e59Rf9H2NQ0ZMgTZ2dlQq9VYv3491q1bh0ceecRy3tfvk//8ZezIzs5Gdna21bGGhgZLS2nEiBGorKy0+rBHR0dDp9NZ7q/T6fxq7NneawKA48eP46GHHsLSpUstV+NmERERWLBgASIiIgAAGRkZKCkp8cuk3vbvbzQaLR9Wf39v2nPx4kXcfffdyMvLw/Tp0y3HBUHArbfeankdWVlZOHr0qN8mitZSUlLQp08fqFQqpKSkoHPnzqiqqkLPnj1l/V5duXIFp0+fRkZGhtVxOb9XAKzGz3U6nWWegFl7/+/5s3//+99Yv3493nrrLctcB7P2PqP+auLEiZb3ZuLEiXj22Wetzvv6fZJd9/trr71maemWlJSgV69eViVihwwZgkOHDkGv10Or1eLUqVMYMGCAVOG65OTJk7j//vuxZs0aZGVl2Zw/c+YM8vLy0NzcDIPBgMOHD2Pw4MESROrc8OHDsXfvXgBAUVGR1d8+NTUVZ8+exeXLl9HY2IiDBw/aTAj0R9XV1bj99tuxZMkSzJ071+pcXV0dpk2bBp1OB0EQsH//fqjVaokidc+2bdvw3HPPAQAqKytRV1eHhIQEAPJ9rwDgwIEDuOGGG2yOy/m9AoBrr70W+/fvBwDs3bsXI0aMsDrf3v97/uqf//wn3n//fbz33nvo3bu3zfn2PqP+qqCgAD/++CMA4LvvvrP5rvb1++T/l3FtLFq0CEuWLME333yD4OBgy0zIDRs2IDk5GRMmTEB+fj7y8vIgCAIefPBBm3Eaf7NmzRo0NjZi5cqVAExXcuvXr7d6TdOnT8e8efMQGhqKGTNmIC0tTeKo7Zs4cSIKCwsxf/58CIKAVatW4dNPP0V9fT1ycnKwbNkyFBQUQBAEzJkzB927d5c6ZKfeeOMNXLlyBa+//jpef/11AKYel4aGBuTk5ODBBx/EggULEBYWhtGjR9u9MPNHc+fOxaOPPorc3FyoVCqsWrUKO3fulPV7BQBlZWVISkqy3G79+ZPrewUAjzzyCJ588km8/PLL6NevH26++WYAwNKlS/HAAw/Y/X/PnzU3N2PlypXo2bMn7r33XgDAyJEjcd9991lek73PqL/3Pjz99NN49tlnERoaim7dulla6mK9T6z9TkREpBCy634nIiIi+5jUiYiIFIJJnYiISCGY1ImIiBSCSZ2IiEgh/HttABG16/z585g8eTJSU1Otjr/xxhtuF+goLy/H+vXrfbIUSqfT4aWXXsJ//vMfREREIDo6Gvfeey9Gjx7t9eciCmRM6kQyd8011+Cf//xnhx/nwoULKC8v90JE1gRBwJ133on09HR89tlnCAsLw9GjR7Fo0SKsWbMG119/vdefkyhQsfudSKGqq6tx1113Yfbs2ZgzZ45lA5DKykoUFBRg3rx5uPHGG/HKK68AMG3vq9Fo8Mwzz2D//v3Iz8+3PNayZcuwfft2S89Abm6uZS+C1atXY9asWfjjH/+Iv//97zZx/Pe//8WFCxfw6KOPIiwsDICpOtrixYstxXzy8/PxwgsvICcnBxMnTsQ333zT7msgIvvYUieSuV9++QUzZsyw3J4+fTr+8pe/YOXKlZgzZw4mTJiAX375BXl5efj444/xr3/9C9OmTcOsWbOg1WqRlZWF/Px8PPHEE3jttdfw1FNPWcqR2lNWVoZ33nkHSUlJ2LRpEwBgx44daGxsREFBAdRqtVUJ059++glqtdqqnDNgqh62Zs0ay22DwYDNmzdj9+7deOWVV5CVleXwNbTeEIOIWjCpE8mco+73ffv24fTp01i7di0AoKmpCeXl5SgoKMD333+Pd999F6WlpTAYDGhoaHD5+bp27Wopw/rdd9/h2LFj+P777wGYdhQ8fvy4VVJXqVRobm62eRyDwWCV6M3bUaalpeHy5cvtvgbzdp1EZI1JnUihjEYjNm7ciM6dOwMwtei7du2K5557DuXl5Zg2bRpuuukm7Nu3D22rRatUKqtjBoPB8u9OnTpZ/t3c3IwlS5Zg0qRJAICamhrLVrVmv/vd7/Dee+/BYDAgNDTUcryoqMhqQxXzHg2tE72j10BE9nFMnUihMjIy8MEHHwAw7QQ4ffp0NDQ0oLCwEAUFBZgyZQrKyspQWVkJo9Fo2dcZALp06YLy8nLo9XpcvnwZhw4dcvgcW7ZsgcFggE6nQ15eHoqKiqzuM2LECPTv3x+rVq2yXBxoNBqsX78ed911l0evgYjsY0udSKGeeOIJLF++3LL/+wsvvIDo6GjccccdWLp0KTp16oQePXpArVbj/PnzSE9Ph1arxZIlS/Diiy8iKysLU6dORWJiIq677jq7zzF//nycPXsWs2bNQlNTE2bPnm13Nvtrr72G//mf/8G0adMQHByMuLg4vPjii05nvjt6DURkH3dpIyIiUgh2vxMRESkEkzoREZFCMKkTEREpBJM6ERGRQjCpExERKQSTOhERkUIwqRMRESkEkzoREZFC/H/7SpI0YieiFgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_model(model, plot = 'boundary')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_model(model, plot = 'feature')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_model(model, plot = 'pr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yZTR79uxrutSRl4CAAD333HOaMGGCgoODNXnyZI0dO1YhISFyOBzq2LGjOnXqpCNHjsjb21vLly/X5MmTVaxYMb333nuy2Wzq27ev3nrrLYWFhblGst54443LPl+LFi1cfXqjP0oLuIvFuNaLnABQyBw5ckQhISGuT5sA+H9cYgAAACaMIAAAABNGEAAAKCR27dqV64ZrOTZs2KDOnTsrPDxcX3zxxTW1xSRFAAAKgblz52rFihUqXrx4ruUZGRmaMGGCFi9erOLFi6t79+5q2bKl6w63V3JDA4LT6VRKSoo8PT1Nn2kHAOCfxjAMZWRkqESJEtf96ZlrkXPfl7/DZrO57kNyOQEBAZo+fbrpY9S//fabAgICXLceb9y4sbZv36527drl+Xw3NCCkpKRo3759N7JJAADyXWBgoPz8/PL1OTIzMxUTvUVepXz/1v42m03169e/Ykho27btZe/uarfbcx1biRIlrukbdm9oQMi5JemWZ0Yp7WTSjWwaN9iLBzdIkqZVb+XmSnAt6K+bR05fGeufvcqW+CfICJ6pffv2uV6/8lNWVpa8SvlqyzOjlXbyzF/at1iFsmr+4UhlZWXlOYpwOb6+vq5br0vZb+avJQzd0ICQc1kh7WSSLh47fSObxg3m7e0tSfTTTYL+unnk9JWRdda9heCaWP53E7WCvCyedvJMgZ7LNWvWVGJios6ePSsfHx9t377ddLO1y2GSIgAAhdDKlSuVmpqq8PBwDRs2TM8884wMw1Dnzp1VsWLFq+5PQAAAoJCoUqWK62OMOd9SKmXfEr9Vq792iZL7IAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADDxcHcBAAAUJU0lGX9xH0t+FHIVjCAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAFAIOJ1OjRgxQuHh4YqIiFBiYmKu9StWrNCjjz6qzp076/PPP79qex75VSgAACg469atk8Ph0KJFixQXF6eoqCi9//77rvUTJ07UqlWr5OPjow4dOqhDhw4qVarUFdsjIAAAUAjExsYqODhYktSgQQPFx8fnWl+nTh1duHBBHh4eMgxDFoslz/YICAAAFAJ2u12+vr6uxzabTZmZmfLwyH6pr127tjp37qzixYurTZs2KlmyZJ7tMQcBAIBCwNfXVykpKa7HTqfTFQ727t2rTZs2af369dqwYYOSkpL0zTff5NkeAQEAgEKgUaNGio6OliTFxcUpMDDQtc7Pz0/FihWTt7e3bDabypQpo/Pnz+fZHpcYAAAoBNq0aaMtW7aoW7duMgxD48eP18qVK5Wamqrw8HCFh4friSeekKenpwICAvToo4/m2R4BAQCAQsBqtWrMmDG5ltWsWdP1c/fu3dW9e/drb++GVQYAAAoNAgIAADDhEgMAAAWoRsU02Sypf2mfrAppOp1P9VwJIwgAAMCEgAAAAEwICAAAwKTIzkEI/SRKJ3fv0w9vf2RaV7v9A3poQqRs3l468XOCVjzzqhwXUmSxWvXw28NU65FgWT1s2jr5I8XOXihJKlOrmjp9+KZ8yt0ihz1VX/UaqjMJBwr6sAqdK/XFpe7u31NN+/dU5sU0nfrlN63uN0Zpyefy7K/Aji0VNi9K5w4dc7XzcXAPOey528a1u56+kqSXT23T+SPHXdtunfShdn++knPLDT7dcERTl///7/hcSoaOnEnT4Y9aq+It3pKkzuO3y7+Mt2Y8f6e7ykQ+u6YRhF27dikiIiK/aykQ5erWUK/183RHl7aXXe9T7haFfjxBX3QeoPfqPqKzBw6rddQQSVLjPt1UNvA2zazfUXObdtG9g55UpabZJ8djn03W9lkLNbNeB20aOV2PL55WYMdUWOXVFzlue/AeNR/6nD596EnNbhim/aujFTIn+3PAefVX1WYNtXXyR5rdMMz1j3Dw911vX5UNrK6LSWdz9cfuz1dK4txyh16tqmjntBbaOa2Ffnr7ft16i7em96nvCgcTl+zX9/9NcnOVyG9XDQhz587V66+/rvT09IKoJ9817ddDOz74Uv/9cs1l19d8+H4djdmtpP3Z36Md8/4C3dkjRJJU99HWivt4qYysLKWdPa/4hV8rqGcn+VWqoHJ1ayh+4deSpP1rouXl66NbG95RMAdVSOXVFzn8G9fTgXVbdeHoCUnSL0vXKjCklayenlfsL0mq0qyhqre6V33iluup6M8UENykYA+ukLnevqrarKGcWU49Ff2Znt+1Qi3e6CeL1cq59Q/w1pLfVKGUt/o8Uk2StGn3aX2745TrMQqvqwaEgIAATZ8+vSBqKRDfDBir+AWrrri+ZNVbdf7w/w9znj9yXMVK+cnLr4RKVfXXucPHcq0rWeVWlazqrwt/nJQM45J1J1Syyq35cxBFRF59kePoj7tUvdW9KhVQSZLU4OnH5OHtJZ+ypa/YX5J08cxZbZ+1ULMbhGr98CkK/2qG/CpXLKAjK3yut6+sHjYdXLdVnz3yrD5u0UM1296vuwdEcG652enzDk1ZdkBTns0OZH+cSdOguXv078iGsjGDrdC76hyEtm3b6siRIwVRyz+CxWrN9Z9RDiPLKYvVkmudxWKRM8spi9Uq48/7WCwysrLyu9xCLa++yHFoc6y+G/2ewr+aIcNpaOdHS5R6JllZjowr9pckfdF5gGv54S2xOrx1p2q2aa64T5bm4xEVXtfbVzs++DLXftumfKy7B0bo6E8/c2650Zw1iQq9p6Jq3FpCGZlOPTF5h6Y8U0/+ZYq5uzQUgCI7SfFKzh06psr33OV6XLJyRV1MOquM1Is6d+iY/CpVcK3zq1RBF44c17lDf8jPv3yudvwqVcg14Qp/XV59kcPLt4R+/+4n7fxosaTs33vLsQN1MensFfvLu5Sfmr7whDZPmO1aZ7FYlJWRWQBHVThdb18F9QzV8V17dXJ3QvbGFoucGZmcW272xeY/NK13fUnS9v3ndOBEqiI/+q8k6XhyurKchtIynPpgwF15NYObFINEf/Lb2s2qcu9dKlMr+/pak+e7ae/y9ZKkhOXr1eBfnWWx2eRdyk/1unXQ3mXrdOHoCSXtP6R64e0lZV+PNZxOndi9z23HURjk1Rc5/CpV0FOb5ruGsoNf66v4BdnXq6/UX44LKWrar4duf+xhSdKtDW5X5buDtH/N9wV4dIXL9fZVhfq11XLMQFmsVnkU89bd/Xtoz6LVnFtulGx3aP+xVDWre4sk6b66t+jQR61dkxf7PBKgx+/3JxwUYowgSPJvXF+dPhin2Q3DlHoqScufHq6ui9+VzctTyb8d0le9hkrKnnh1S80APb9ruWxenoqdvUiJ0TGSpCXdX1LI3LFq8XpfZaY59GXXFy875Iprd6W+uLS/zuw7qM1Rc/Tsj1/KYrXq8OZYre6fPTM+r/5aGPqC2k1/XQ+OHiBnZpYWhw/WxTPJ7jzcm9r19tWm0TPUfsYI9d29UlZPD/33yzWuyw6cW+6x/1iq/G/xlqcH7yOLKothusD396Wnpys+Pl7rQwbq4rGCvms0/oqRRvZQ7mhLHTdXgmtBf908cvrKWBlylS3xT+B4eLHi4+NVv359eXt75+tz5bxGlnu2t2wnT/6lfbMqVNDpD+YUSJ05iIYAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATDzcXQAAAEVJ+Tt95X0u7S/tk17KV6fzqZ4rYQQBAACYEBAAAIAJAQEAAJgQEAAAgAkBAQAAmBAQAACACQEBAACYEBAAAIAJAQEAAJgQEAAAgAkBAQAAmBAQAACACQEBAACYEBAAAIAJAQEAAJgQEAAAgImHuwsAAADXz+l0atSoUUpISJCXl5fGjRunatWqudb//PPPioqKkmEYKl++vCZNmiRvb+8rtscIAgAAhcC6devkcDi0aNEiRUZGKioqyrXOMAy98cYbmjBhghYsWKDg4GAdPXo0z/YYQQAAoBCIjY1VcHCwJKlBgwaKj493rTt48KBKly6tefPmad++fXrggQdUo0aNPNtjBAEAgELAbrfL19fX9dhmsykzM1OSlJycrJ07d+qJJ57Qxx9/rG3btumHH37Isz0CAgAAhYCvr69SUlJcj51Opzw8si8UlC5dWtWqVVOtWrXk6emp4ODgXCMMl0NAAACgEGjUqJGio6MlSXFxcQoMDHStq1q1qlJSUpSYmChJ2r59u2rXrp1ne8xBAACgEGjTpo22bNmibt26yTAMjR8/XitXrlRqaqrCw8P15ptvKjIyUoZhqGHDhnrwwQfzbI+AAABAIWC1WjVmzJhcy2rWrOn6+b777tPixYuvvb0bVhkAACg0CAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEy4kyIAAAXIck9pWdKdf20f79L5U0weGEEAAAAmBAQAAGBCQAAAACYEBAAAYEJAAAAAJgQEAABgQkAAAAAmBAQAAGBCQAAAACYEBAAAYEJAAAAAJgQEAABgQkAAAAAmBAQAAGBCQAAAACYEBAAAYOKRH42+eHCDvL2986Np3GAjjQR3l4C/gP66eVhCVrq7BFyL9HR3V/CPxQgCAAAwyZcRhGnVW+nisdP50TRukJx3oqMtddxcCa4F/XXzyOmrrNB6bq4E1+SLHe6u4B+LEQQAAGBCQAAAACYEBAAAYEJAAAAAJgQEAABgQkAAAAAmBAQAAGBCQAAAACYEBAAAYEJAAAAAJgQEAABgQkAAAAAmBAQAAGBCQAAAACYEBAAAYOLh7gIAAChKLNVLypLl/Gv72ErmUzVXxggCAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAhYDT6dSIESMUHh6uiIgIJSYmXna7N954Q5MnT75qewQEAAAKgXXr1snhcGjRokWKjIxUVFSUaZuFCxdq375919QeAQEAgEIgNjZWwcHBkqQGDRooPj4+1/qdO3dq165dCg8Pv6b2CAgAABQCdrtdvr6+rsc2m02ZmZmSpJMnT2rGjBkaMWLENbfH1z0DAFAI+Pr6KiUlxfXY6XTKwyP7ZX7NmjVKTk5W7969derUKaWlpalGjRp67LHHrtgeAQEAgEKgUaNG2rhxo9q3b6+4uDgFBga61vXq1Uu9evWSJC1dulQHDhzIMxxIBAQAAAqFNm3aaMuWLerWrZsMw9D48eO1cuVKpaamXvO8g0sREAAAKASsVqvGjBmTa1nNmjVN211t5MDV3g2pCgAAFCoEBAAAYEJAAAAAJgQEAABgQkAAAAAmBAQAAGBCQAAAACYEBAAAYEJAAAAAJgQEAABgQkAAAAAmBAQAAGBCQAAAACYEBAAAYEJAAAAAJgQEAABg4uHuAgAAKFJq1JKsqX9tH6ePlJI/5VwJIwgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwMTD3QUUtNrtH9BDEyJl8/bSiZ8TtOKZV+W4kJJrm7v791TT/j2VeTFNp375Tav7jVFa8jl5l/RVpw/fVLm6NWSxWrVr3jJtmThXknTbg/eozaRXZPX0UObFNH0zcJz+iNntjkMsdEI/idLJ3fv0w9sfmdZdqT8tVqsefnuYaj0SLKuHTVsnf6TY2QslSWVqVVOnD9+UT7lb5LCn6qteQ3Um4UBBH1ahcz3nliQ16fuEGj3bRR7Fi+lY7B6teOZVZTkyFNixpcLmRencoWOudj4O7iGHPXfbuLFmHEjSzINJKm6zqK6ft6bf6a/nd/2h31Icrm0OpmaoRVkfLbsnwI2VIr9cdQTB6XRqxIgRCg8PV0REhBITEwuirnzhU+4WhX48QV90HqD36j6iswcOq3XUkFzb3PbgPWo+9Dl9+tCTmt0wTPtXRytkzhhJUsuxL+r8kRN6/84QzW3aRU36dlOVexvI6umpLoumauVzr2t2g1BFj3tfj86f5I5DLFTK1a2hXuvn6Y4ubS+7Pq/+bNynm8oG3qaZ9TtqbtMuunfQk6rU9E5J0mOfTdb2WQs1s14HbRo5XY8vnlZgx1RYXe+5VffRNrp7QE992vppzazXQR7FvXXv4KckSVWbNdTWyR9pdsMw1z/CQf7aeDpFk/af1tpm1RT7YE21q+Cr53f9oS+aVlXsgzUV+2BNzbqrkkp72jQ9yN/d5SKfXDUgrFu3Tg6HQ4sWLVJkZKSioqIKoq58UfPh+3U0ZreS9meHnJj3F+jOHiG5tvFvXE8H1m3VhaMnJEm/LF2rwJBWsnp6as2Lb2rtkLckSb7+5WXz9lLauQtyZmRoSuUWOh73iyTplhpVdfFMcgEeWeHUtF8P7fjgS/33yzWXXZ9Xf9Z9tLXiPl4qIytLaWfPK37h1wrq2Ul+lSqoXN0ail/4tSRp/5poefn66NaGdxTMQRVS13tu3dUrTD+8/VH2aIJh6OvnR+rn+cslSVWaNVT1VveqT9xyPRX9mQKCmxTswRVBO85e1EPlS6hKcU9J0qP+JbXqhF0OpyFJcjgN/WvnUU2pX1FV/7cNCp+rBoTY2FgFBwdLkho0aKD4+Ph8Lyq/lKx6q84fPu56fP7IcRUr5ScvvxKuZUd/3KXqre5VqYBKkqQGTz8mD28v+ZQtLUkysrL06PxJeiF+lX7f9JPOJByUJDkzM1WiQlkNPhKtNpNe0ZaJHxTcgRVS3wwYq/gFq664Pq/+LFXVX+cOH8u1rmSVW1Wyqr8u/HFSMoxL1p1QySq35s9BFBHXe26VDbxNJSqUVY9vPtDzu1bowVEDlHb2giTp4pmz2j5roWY3CNX64VMU/tUM+VWuWLAHWMTcfUtxbTydosTU7MsJnxw+K4fT0BlHpiTpo8Rk+RfzVJh/SXeWiXx21YBgt9vl6+vremyz2ZSZmZmvReUXi9Wa64Uhh5HldP18aHOsvhv9nsK/mqHnYpbIcBpKPZOsLEeGa5uvIl7WxHL3qniZUnpgRD/X8pSTZzS1Sgt9eF+4Qj+eoDK1b8vX4ynq8upPi9WSa53FYpEzyymL1Srjz/tYLDKysvK73ELtes8tq6eHarRpri8ff1FzmnRWsTKl1OrNwZKkLzoP0C9LvpUkHd4Sq8Nbd6pmm+YFc2BFVHDZEnojsLy6xBzRPd8dkFVSGU+bvKwWSdK0A0l6NbCce4tEvrtqQPD19VVKyv9f73M6nfLwuDnnNp47dEy+lSq4HpesXFEXk84qI/Wia5mXbwn9/t1PmtP4Mc1t2lkJy9dJki4mnVXNh++Xr3/2/hkpqYpf8LVubXSHvEv6qm5Ya1cbx3f+Vyd27VXFOwML6MiKprz689yhY/K7ZJ1fpQq6cOS4zh36Q37+5XO141epgs4fOS78fdd7bl3446T2Ll0rx4UUOTMytPvfK1TlvgbyLuWn+4f3yfVcFotFWRk355uUm8WFzCy1KFtCMQ/U0I8P1FCnW/0kZYeEnecuKtMw9EBZHzdXifx21YDQqFEjRUdHS5Li4uIUGHjzvuj9tnazqtx7l8rUqiZJavJ8N+1dvj7XNn6VKuipTfNdQ6PBr/VV/ILs69X1Hm+nB0dmjxjYvDxV7/F2+n3DNjmznOr00XhVbdZIklT+jloqV7eGjvy4q6AOrUjKqz8Tlq9Xg391lsVmk3cpP9Xr1kF7l63ThaMnlLT/kOqFt5eUfe3ccDp1Yvc+tx1HYXC959Yvi7/VHY+3k0cxb0lS3bDW+iNmtxwXUtS0Xw/d/tjDkqRbG9yuyncHaf+a7wvq0IqkP9Iy9dDW33U+I3tkbcKvp9WtcklZLBZFn05Vy3IlZLFY3Fwl8ttVhwLatGmjLVu2qFu3bjIMQ+PHjy+IuvJF6qkkLX96uLouflc2L08l/3ZIX/UaKv/G9dXpg3Ga3TBMZ/Yd1OaoOXr2xy9lsVp1eHOsVvfPnmn9bWSUOs4arb67V0qS9n61TtumfSoZhhaF9VPbd16VzdNDmekOLXliiGsyFm6cS/vqSv0pZU+Su6VmgJ7ftVw2L0/Fzl6kxOgYSdKS7i8pZO5YtXi9rzLTHPqy64uXHR7Htbvecytm5ucqXqaUesculcVm07Ede/RtZJQMp1MLQ19Qu+mv68HRA+TMzNLi8MFMAs5ndXy99Urtcmr2/UE5Dal5WR+9e2f2PJ39KQ5V82FiYlFgMUwXZP++9PR0xcfHa33IQF08dvpGNYt8MNJIkCSNttRxcyW4FvTXzSOnr7JC67m5ElyLzC92KD4+XvXr15e3t3e+PlfOa2S9EqvkbU39a/s6fbQnpWOB1JmDOykCAAATAgIAADAhIAAAABMCAgAAMLk5b2gAAMBNynJLbVk8M66+4aX7ZHhKBfwVJIwgAAAAEwICAAAwISAAAAAT5iAAAFAIOJ1OjRo1SgkJCfLy8tK4ceNUrVo11/pVq1Zp3rx5stlsCgwM1KhRo2S1XnmcgBEEAAAKgXXr1snhcGjRokWKjIxUVFSUa11aWpreeecdffrpp1q4cKHsdrs2btyYZ3sEBAAACoHY2FgFBwdLkho0aKD4+HjXOi8vLy1cuFDFixeXJGVmZl71ls0EBAAACgG73S5fX1/XY5vNpszM7K9Gt1qtKleunCRp/vz5Sk1NVfPmzfNsjzkIAAAUAr6+vkpJ+f+bJTidTnl4eOR6PGnSJB08eFDTp0+/6ld2M4IAAEAh0KhRI0VHR0uS4uLiFBgYmGv9iBEjlJ6erpkzZ7ouNeSFEQQAAAqBNm3aaMuWLerWrZsMw9D48eO1cuVKpaamqn79+lq8eLGaNGmiJ598UpLUq1cvtWnT5ortERAAACgErFarxowZk2tZzZo1XT/v3bv3r7V3Q6oCAACFCgEBAACYEBAAAIAJAQEAAJgQEAAAgAkBAQAAmBAQAACACQEBAACYEBAAAIAJAQEAAJgQEAAAgAkBAQAAmBAQAACACQEBAACYEBAAAIAJAQEAAJgQEAAAgAkBAQAAmBAQAACACQEBAACYEBAAAIAJAQEAAJgQEAAAgImHuwsAAKBIKV1H8v6L+6RLOpIfxVwZIwgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAAEwICAAAwISAAAAATAgIAADAhIAAAABMCAgAAMCEgAAAQCHgdDo1YsQIhYeHKyIiQomJibnWb9iwQZ07d1Z4eLi++OKLq7ZHQAAAoBBYt26dHA6HFi1apMjISEVFRbnWZWRkaMKECfroo480f/58LVq0SKdOncqzPY8bWZxhGJKkvglr5OXldSObxg2Wnp4uSRqW9rObK8G1oL9uHjl9pS92uLcQXBOHwyHp/1+/CkJGRv7sExsbq+DgYElSgwYNFB8f71r322+/KSAgQKVKlZIkNW7cWNu3b1e7du2u2N4NDQgZ/zuCffv23chmAQDIVxkZGSpWrFi+PofNZpPNZlNCQtZ17X8ldrtdvr6+ubbPzMyUh4eH7Ha7/Pz8XOtKlCghu92e5/Pd0IBQokQJBQYGytPTUxaL5UY2DQDADWcYhjIyMlSiRIl8fy4PDw/Vr19fWVl/PyB4eFz5ZdvX11cpKSmux06n07X9n9elpKTkCgyXrfdvVXkFVqv1qk8IAMA/SX6PHFzKw8Mjzxf569GoUSNt3LhR7du3V1xcnAIDA13ratasqcTERJ09e1Y+Pj7avn27nnnmmTzbsxgFeeEFAADkC6fTqVGjRmnfvn0yDEPjx4/Xf//7X6Wmpio8PFwbNmzQe++9J8Mw1LlzZ/Xo0SPP9ggIAADAhI85AgAAEwICAAAwISAAAAATAgIKvf379yszM9PdZeBPnE6nu0tAPmBaW+FBQLhB/u7nWpG/vvnmG73//vvas2cPIeEf4uOPP9a5c+dktVoJCYVIUlKSJHEPnEKEgHADOJ1O2Ww2GYahXbt26fjx4+4uqcgzDENTp07VQw89pKCgIC1fvpyQ8A9gt9u1du1azZo1S2fPniUkFBIOh0Nbt27V4sWLtX37dmVlZdGvhQAB4TplZWXJarXKMAwNHDhQUVFRmjt3rtatW+fu0oo0i8WihIQERUZGqnv37goICNCyZcsICW7idDr14YcfKiYmRunp6fLw8NDbb79NSCgEDMOQl5eXLBaL3nnnHS1dulQ2m41+LQQICNcpZ+Tgww8/VOPGjfXJJ5+oTp06iouL07fffuvu8oqknO8EmTVrlvz8/DRw4EA98cQTqlatmlauXKm4uDguCRWwmTNnateuXWrYsKG6deumnj17qkyZMpoyZQoh4SbmdDpdlxT27dunpk2bqmzZslq2bJmk7Lvr4uZF7/1Nl/5ntn37di1atEje3t7y9vbWQw89JH9/f8XGxurMmTNurLLocTqd8vT0VFJSko4cOaLx48erWrVqGjBggJ544gmVL19e69evZxShgIWEhOj333/XsGHDVK9ePVWsWFGPPvqoypcvr3HjxrnmJODmkhPsBg8erBo1amjy5MkKCgrSvn37NHXqVP3nP/8hjN/E8ueG0IVcVlaWa+QgISFBgYGBGjp0qD7//HPVrl1bTZo0Ubt27ZSenq6yZcu6u9wiwzAMWa1WnTx5UgMGDFD16tXlcDg0ZcoURUVF6amnntInn3yi1NRUeXt7u7vcIqVq1ary8PDQ/v37XZPZqlWrpvbt2+s///mP6yt3cXMwDMM1crBz505988036tGjh2w2m5o0aSJPT08tWbJE9913X57fPoh/Nm61/Dc5nU716dNHZcqUUVxcnIYPH67k5GQtWLBAgwcP1n333efuEoukCxcuaPDgwa5LCq+//roCAwM1cuRITZs2Td26dZO/v7+7yyySkpKSdPjwYU2YMEFPP/202rZtKyn7kpCnp6ebq8O1cjqdrnlXp0+fVvny5bVu3TqNGDFCs2bNUlBQkLKyspSVlSUvLy93l4vrQED4Cw4fPix/f395eHhowoQJslqtGjp0qGJiYjRhwgRNmjRJv/zyi6pWraq77rrL3eUWGTkjOlL2LPnVq1erevXqWrp0qYKDg/XJJ58oICBAkydPdnOlkKTo6GhFRUUpMjJSDz30kLvLwV+QM3LgdDo1cOBA+fn5aceOHYqKilJaWpr69eunefPm6c4773R3qbgBuMRwjX744QfZ7XZVrVpVkuTv7+9619O0aVO1atVKu3fvVlhYmBurLHpyPmJ64sQJbdq0SQEBAapTp46+//57de7cWU6nU4GBgerdu7e7S8X/tGjRQp6enq5zCTePnMsKw4cPV/Xq1RUZGalt27apX79+WrZsmV599VXZ7XY3V4kbhYBwjXIuGcybN0+1atWSj4+Pjh49qnXr1qlkyZJau3atRo0a5d4iiyCr1apTp07plVdeUWBgoAIDA3XXXXdpzZo1WrFihbZu3arZs2crICDA3aXiElyCu7lcOudAksqXL6/Q0FBJ0r333qvHH39chw4dUpcuXS67PW5OTBu+ij/PwE1JSdH333+vSpUqycfHR7t379YHH3ygoUOHqlGjRm6qsmjK+STJ0qVLdccdd+i1115Tw4YN9dNPP8nX11ft2rXTJ598opo1a7q5UuDmlfNibxiGdu7cKbvdrvPnz2vBggWy2+3asWOHNm3alGu+AeGgcGAEIQ85k6ecTqfGjh2revXq6YUXXtAnn3yimJgY3XPPPWrWrJnOnz+vkiVLurvcIuPSSVJS9gx5q9Wq1NRU+fj4KDY2Vv7+/rxLBa7TpeGgX79+SktLU+nSpdW6dWutWLFCkydPVkJCgl5++WUFBQW5u1zcYASEPOTMMRgwYICaNm2qChUqaO3atWrevLm+/vprrVq1SvXr15efn5+bKy06csLByZMn9dlnn6lOnTpKS0vTjz/+KE9PT6Wmpmrbtm1c7gFugJxw8Nprr6lx48Z65plntHjxYm3dulUjRoxQxYoVlZSUpPLly7u7VOQDLjFcxrJly7RgwQJJ0vHjx2W32xUcHKzPP/9cMTExmjFjhvr27av+/furZMmSDKcVkJxwkJSUpOeee07Vq1fXmjVrdPDgQXXq1EmlS5eW0+nU6NGjVaNGDXeXC9y0Lr0R3PHjx7Vnzx4dPnxYktSlSxelp6drz549stlsKleunLvKRD4jIFxGWFiYunfvrilTpujWW2/VXXfdpZ9++knPP/+8XnzxRSUnJyspKUmVKlVyd6lFRk44OHv2rBISEtSlSxeFhYXp1KlTKl26tMqXL6+wsDD1799f1atXd3e5wE0r54ZjTqdTP/zwg5KSkjRjxgzZ7XbNmDFDiYmJ+v3333XrrbdKYr5BYcZ9EC5x6efpJalv376yWCyaOXOm9uzZozVr1mjTpk0aMmSIHnjgATdWWjQlJyerT58+evjhhzVv3jyVLl1an376qeLi4rRkyRK99dZb8vHx4T8s4G+6dM7BwIEDXY99fHzUv39/DRo0SHa7XZMmTXLdEIk7JRZejCD8T87n6XMmJE6bNk3Tpk2Tj4+PevfurXr16ql9+/aKiooiHLiB0+nUmjVrlJmZqdatW2vgwIFKSUnRunXrNG3aNA0aNEglSpQgHADXIScczJw5UwEBAZoxY4amTp0qu92u+Ph4TZw4UdWqVdO2bdskiXBQyBEQ/ifni2L69eunEiVK6O6775aXl5fGjRun4sWLKyIiQrfffrvq1avn5kqLJqvVqrZt2+rhhx/WwoULVb9+fb333nvy9fXVu+++q1q1arm7RKBQOHPmjGJiYiRJ58+fl4eHh5o2bSqHw6GaNWtqyJAh2r17t+s7NVB4FflLDJfe0OPYsWMaO3asZs6cKUnav3+/5syZo4kTJyohIUF16tRxZ6lQ9v38V6xYoQMHDujpp59mvgFwA+TM8enXr5969uypqlWratq0aWratKlKly6tjz76SIMGDdK9994rSXI4HHzPQhFQpEcQsrKycg1JV6hQQb6+vpoyZYokydvbW+fPn9fZs2cJB/8QZcqUUUhIiGrXrs29J4DrlPP+MGcENSQkRMOGDXN9I+rmzZu1YMECPffcc65wIIlwUEQU2RGEP3/pSI0aNbR//3716dNHCxYs0Pnz53Xq1Cn17dtXrVq1cne5+BMmRwHX59LR0w8++EBhYWEqV66cvvvuO7300kuaOXOmKlWqpBkzZui+++5TixYtVKZMGTdXjYJUJAPCpSfGkCFD1LBhQ7Vr106PP/642rVrp/79++vXX3+Vr6+vbrvtNvcWCwA32KV3I924caM2bNggLy8vvfDCCypXrpzeeustffvtt9qwYYM2bdqkjRs3KjIyklG7IqbIBYScEyPHjBkz1KRJE82fP1+dO3dWUlKS6tevr7p167qxSgDIX06nU4MHD1aFChUUFBSkX3/9VcnJyWrTpo1WrFih7t27q3HjxpKkixcvqnjx4m6uGAWtSM1ByLkBiGEYevXVV7Vs2TIlJSXprbfeUrNmzVSvXj19+umnKmKZCUARNH78eJUvX14DBgzQ1q1bdfbsWe3du1ezZ89Wp06d1LhxY9cdFQkHRVOR+S6GS69ZDxkyRMWLF1dYWJjuvPNOnT59Wna7XZGRkYqMjNTtt9/u5moBIH9VrVpVhw8f1siRI9W6dWudOHFCrVq1UqNGjVyXEi4dbUXRUyQCwqU3Qfrpp5909OhRZWZmKjExUTVr1tTw4cNVrFgxtW7dmq8GBlAkhISEKCUlRQcPHlS5cuX06aefasiQIcwzgEuhn4Nw6a1D+/btqwoVKujkyZPatGmT6tevr6lTp6pq1aruLhMACtzFixe1atUqrVq1Sk8//bQefPBBd5eEf5BCHxByvPfeezpy5IgmTJggwzA0aNAgRUdHq3Llylq8eLGKFSvm7hIBoMAZhqELFy4wcgCTInGJ4cKFC0pLS9OZM2e0d+9e1a1bVyEhIXrkkUdUv359wgGAIstisRAOcFlFZgTh3LlzWrp0qY4cOaIaNWpo+fLlevHFF9W8eXN3lwYAwD9OkZmiWqpUKYWGhuqWW27R6tWr1bVrVzVv3pyPNAIAcBlF4hJDjjJlyqhnz57y8fFRQkKC63IDAADIrciMIOQoXbq0QkNDddttt6lcuXLuLgcAgH+kIjMH4c/4sh8AAK6syAYEAABwZUXuEgMAALg6AgIAADAhIAAAABMCAgAAMCEgAAAAk/8DvPfxusR44O4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x396 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_model(model, plot = 'class_report')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x684 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interpret_model(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_835c4_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Model</th>        <th class=\"col_heading level0 col1\" >Accuracy</th>        <th class=\"col_heading level0 col2\" >AUC</th>        <th class=\"col_heading level0 col3\" >Recall</th>        <th class=\"col_heading level0 col4\" >Prec.</th>        <th class=\"col_heading level0 col5\" >F1</th>        <th class=\"col_heading level0 col6\" >Kappa</th>        <th class=\"col_heading level0 col7\" >MCC</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_835c4_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_835c4_row0_col0\" class=\"data row0 col0\" >CatBoost Classifier</td>\n",
       "                        <td id=\"T_835c4_row0_col1\" class=\"data row0 col1\" >0.9591</td>\n",
       "                        <td id=\"T_835c4_row0_col2\" class=\"data row0 col2\" >0.9912</td>\n",
       "                        <td id=\"T_835c4_row0_col3\" class=\"data row0 col3\" >0.9054</td>\n",
       "                        <td id=\"T_835c4_row0_col4\" class=\"data row0 col4\" >1.0000</td>\n",
       "                        <td id=\"T_835c4_row0_col5\" class=\"data row0 col5\" >0.9504</td>\n",
       "                        <td id=\"T_835c4_row0_col6\" class=\"data row0 col6\" >0.9157</td>\n",
       "                        <td id=\"T_835c4_row0_col7\" class=\"data row0 col7\" >0.9189</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1a5fd4f77c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>id</th>\n",
       "      <th>texture_mean</th>\n",
       "      <th>perimeter_mean</th>\n",
       "      <th>area_mean</th>\n",
       "      <th>smoothness_mean</th>\n",
       "      <th>compactness_mean</th>\n",
       "      <th>concavity_mean</th>\n",
       "      <th>concave points_mean</th>\n",
       "      <th>symmetry_mean</th>\n",
       "      <th>fractal_dimension_mean</th>\n",
       "      <th>...</th>\n",
       "      <th>area_worst</th>\n",
       "      <th>smoothness_worst</th>\n",
       "      <th>compactness_worst</th>\n",
       "      <th>concavity_worst</th>\n",
       "      <th>concave points_worst</th>\n",
       "      <th>symmetry_worst</th>\n",
       "      <th>fractal_dimension_worst</th>\n",
       "      <th>diagnosis</th>\n",
       "      <th>Label</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>88147104.0</td>\n",
       "      <td>15.460000</td>\n",
       "      <td>66.620003</td>\n",
       "      <td>329.600006</td>\n",
       "      <td>0.10530</td>\n",
       "      <td>0.07722</td>\n",
       "      <td>0.006643</td>\n",
       "      <td>0.01216</td>\n",
       "      <td>0.1788</td>\n",
       "      <td>0.06450</td>\n",
       "      <td>...</td>\n",
       "      <td>395.399994</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.1153</td>\n",
       "      <td>0.02639</td>\n",
       "      <td>0.04464</td>\n",
       "      <td>0.2615</td>\n",
       "      <td>0.08269</td>\n",
       "      <td>B</td>\n",
       "      <td>B</td>\n",
       "      <td>0.9995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9012795.0</td>\n",
       "      <td>15.100000</td>\n",
       "      <td>141.300003</td>\n",
       "      <td>1386.000000</td>\n",
       "      <td>0.10010</td>\n",
       "      <td>0.15150</td>\n",
       "      <td>0.193200</td>\n",
       "      <td>0.12550</td>\n",
       "      <td>0.1973</td>\n",
       "      <td>0.06183</td>\n",
       "      <td>...</td>\n",
       "      <td>1535.000000</td>\n",
       "      <td>0.1192</td>\n",
       "      <td>0.2840</td>\n",
       "      <td>0.40240</td>\n",
       "      <td>0.19660</td>\n",
       "      <td>0.2730</td>\n",
       "      <td>0.08666</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>0.9901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>877500.0</td>\n",
       "      <td>20.219999</td>\n",
       "      <td>94.489998</td>\n",
       "      <td>642.700012</td>\n",
       "      <td>0.09872</td>\n",
       "      <td>0.12060</td>\n",
       "      <td>0.118000</td>\n",
       "      <td>0.05980</td>\n",
       "      <td>0.1950</td>\n",
       "      <td>0.06466</td>\n",
       "      <td>...</td>\n",
       "      <td>1044.000000</td>\n",
       "      <td>0.1552</td>\n",
       "      <td>0.4056</td>\n",
       "      <td>0.49670</td>\n",
       "      <td>0.18380</td>\n",
       "      <td>0.4753</td>\n",
       "      <td>0.10130</td>\n",
       "      <td>M</td>\n",
       "      <td>M</td>\n",
       "      <td>0.9932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86408.0</td>\n",
       "      <td>20.760000</td>\n",
       "      <td>82.150002</td>\n",
       "      <td>480.399994</td>\n",
       "      <td>0.09933</td>\n",
       "      <td>0.12090</td>\n",
       "      <td>0.106500</td>\n",
       "      <td>0.06021</td>\n",
       "      <td>0.1735</td>\n",
       "      <td>0.07070</td>\n",
       "      <td>...</td>\n",
       "      <td>527.400024</td>\n",
       "      <td>0.1287</td>\n",
       "      <td>0.2250</td>\n",
       "      <td>0.22160</td>\n",
       "      <td>0.11050</td>\n",
       "      <td>0.2226</td>\n",
       "      <td>0.08486</td>\n",
       "      <td>B</td>\n",
       "      <td>B</td>\n",
       "      <td>0.9532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>912193.0</td>\n",
       "      <td>18.030001</td>\n",
       "      <td>78.290001</td>\n",
       "      <td>455.299988</td>\n",
       "      <td>0.09087</td>\n",
       "      <td>0.07838</td>\n",
       "      <td>0.029160</td>\n",
       "      <td>0.01527</td>\n",
       "      <td>0.1464</td>\n",
       "      <td>0.06284</td>\n",
       "      <td>...</td>\n",
       "      <td>547.400024</td>\n",
       "      <td>0.1208</td>\n",
       "      <td>0.2279</td>\n",
       "      <td>0.16200</td>\n",
       "      <td>0.05690</td>\n",
       "      <td>0.2406</td>\n",
       "      <td>0.07729</td>\n",
       "      <td>B</td>\n",
       "      <td>B</td>\n",
       "      <td>0.9991</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id  texture_mean  perimeter_mean    area_mean  smoothness_mean  \\\n",
       "0  88147104.0     15.460000       66.620003   329.600006          0.10530   \n",
       "1   9012795.0     15.100000      141.300003  1386.000000          0.10010   \n",
       "2    877500.0     20.219999       94.489998   642.700012          0.09872   \n",
       "3     86408.0     20.760000       82.150002   480.399994          0.09933   \n",
       "4    912193.0     18.030001       78.290001   455.299988          0.09087   \n",
       "\n",
       "   compactness_mean  concavity_mean  concave points_mean  symmetry_mean  \\\n",
       "0           0.07722        0.006643              0.01216         0.1788   \n",
       "1           0.15150        0.193200              0.12550         0.1973   \n",
       "2           0.12060        0.118000              0.05980         0.1950   \n",
       "3           0.12090        0.106500              0.06021         0.1735   \n",
       "4           0.07838        0.029160              0.01527         0.1464   \n",
       "\n",
       "   fractal_dimension_mean  ...   area_worst  smoothness_worst  \\\n",
       "0                 0.06450  ...   395.399994            0.1341   \n",
       "1                 0.06183  ...  1535.000000            0.1192   \n",
       "2                 0.06466  ...  1044.000000            0.1552   \n",
       "3                 0.07070  ...   527.400024            0.1287   \n",
       "4                 0.06284  ...   547.400024            0.1208   \n",
       "\n",
       "   compactness_worst  concavity_worst  concave points_worst  symmetry_worst  \\\n",
       "0             0.1153          0.02639               0.04464          0.2615   \n",
       "1             0.2840          0.40240               0.19660          0.2730   \n",
       "2             0.4056          0.49670               0.18380          0.4753   \n",
       "3             0.2250          0.22160               0.11050          0.2226   \n",
       "4             0.2279          0.16200               0.05690          0.2406   \n",
       "\n",
       "   fractal_dimension_worst  diagnosis  Label   Score  \n",
       "0                  0.08269          B      B  0.9995  \n",
       "1                  0.08666          M      M  0.9901  \n",
       "2                  0.10130          M      M  0.9932  \n",
       "3                  0.08486          B      B  0.9532  \n",
       "4                  0.07729          B      B  0.9991  \n",
       "\n",
       "[5 rows x 33 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_holdouts = predict_model(model)\n",
    "pred_holdouts.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Leveraging `PyCaret` results in a <mark>**model prediction accuracy of 96%**</mark> on the holdout set.\n",
    "\n",
    "************************************\n",
    "## Breast Cancer Detection - Deep Learning \n",
    "### with fastai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import packages\n",
    "from os import listdir\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from fastai.callback.fp16 import *\n",
    "from fastai.vision.all import *\n",
    "from fastai import *\n",
    "from fastai.metrics import error_rate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "277524"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = \"./data/images/IDC_regular_ps50_idx5\"\n",
    "files = get_image_files(path)\n",
    "len(files)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Load training data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Due to IPython and Windows limitation, python multiprocessing isn't available now.\n",
      "So `number_workers` is changed to 0 to avoid getting stuck\n"
     ]
    }
   ],
   "source": [
    "pattern= r'([^/_]+).png$'\n",
    "dls = ImageDataLoaders.from_path_re(path, files, pattern, item_tfms=Resize(50),\n",
    "                                    bs=64, size=50, valid_pct=0.3, seed = 61)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Class 0 = benign, class 1 = malignant\n",
    "dls.show_batch()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modeling \n",
    "\n",
    "I've been learning the [fastai](https://docs.fast.ai/) deep learning library, which also leverages `PyTorch`. The documentation is (IMHO) not well organized, but that is more than made up for with the online courses and the accompanying book. `fastai` streamlines much of the neural network modeling details, allowing me to simply supply model names such as `ResNet18` to the `cnn_learner` method. In addition, many of these models are pre-trained through *transfer learning*, requiring the model to only need to learn the weights of the last layer of the network.  \n",
    "\n",
    "With transfer learning, we begin with an existing (trained) neural network used for image recognition and then tweak it a bit to train a model for a particular use case. Training a reasonable neural network would mean needing approximately 300,000 image samples, and to achieve really good performance, we’re going to need at least a million images. For this use case, there are approximately 222,000 images in the training set. I am leveraging the `cnn_learner` function for loading a pre-trained `ResNet34` network that was trained on around a million images from the ImageNet database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fastai has a pretty cool feature that forces half-precision floating point\n",
    "# precision training, effectively reducing GPU memory consumption: to_fp16\n",
    "learn = cnn_learner(dls, models.resnet34, metrics=[accuracy]).to_fp16()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**As a baseline, I will run two different variations of the `fine-tune` method, which takes a pre-trained model and uses one epoch to fit just those parts necessary to fit my dataset.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.341597</td>\n",
       "      <td>0.319248</td>\n",
       "      <td>0.862582</td>\n",
       "      <td>1:58:14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.272603</td>\n",
       "      <td>0.272337</td>\n",
       "      <td>0.886088</td>\n",
       "      <td>16:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.269025</td>\n",
       "      <td>0.255816</td>\n",
       "      <td>0.894507</td>\n",
       "      <td>10:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.221711</td>\n",
       "      <td>0.248075</td>\n",
       "      <td>0.896165</td>\n",
       "      <td>11:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.127272</td>\n",
       "      <td>0.298969</td>\n",
       "      <td>0.893546</td>\n",
       "      <td>11:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.058947</td>\n",
       "      <td>0.411077</td>\n",
       "      <td>0.889571</td>\n",
       "      <td>11:13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 2h 58min 11s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Run a simple fine-tune for 5 epochs\n",
    "learn.fine_tune(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Path('data/images/IDC_regular_ps50_idx5/models/BCPD_Simple5.pth')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn.save('BCPD_Simple5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn.load('BCPD_Simple5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.recorder.plot_loss()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Accuracy peaks at 3 epochs, so we only need to train that far. 89.6% accuracy is good, but I'd really like to see it break 90. I am going to retrain the model on only 3 epochs and then unfreeze all the weights and train the whole model again...**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.348063</td>\n",
       "      <td>0.320960</td>\n",
       "      <td>0.862846</td>\n",
       "      <td>14:40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.291008</td>\n",
       "      <td>0.268660</td>\n",
       "      <td>0.885679</td>\n",
       "      <td>11:49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.237887</td>\n",
       "      <td>0.245006</td>\n",
       "      <td>0.897498</td>\n",
       "      <td>11:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.178940</td>\n",
       "      <td>0.254605</td>\n",
       "      <td>0.896862</td>\n",
       "      <td>10:32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 48min 10s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "learn.fine_tune(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "AttributeError",
     "evalue": "'Sequential' object has no attribute 'plot'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<timed exec>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n",
      "\u001b[1;32mD:\\Users\\David\\anaconda3\\lib\\site-packages\\fastcore\\basics.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, k)\u001b[0m\n\u001b[0;32m    386\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_component_attr_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    387\u001b[0m             \u001b[0mattr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_default\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 388\u001b[1;33m             \u001b[1;32mif\u001b[0m \u001b[0mattr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mattr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    389\u001b[0m         \u001b[1;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    390\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__dir__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mcustom_dir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_dir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Users\\David\\anaconda3\\lib\\site-packages\\fastcore\\basics.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, k)\u001b[0m\n\u001b[0;32m    386\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_component_attr_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    387\u001b[0m             \u001b[0mattr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_default\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 388\u001b[1;33m             \u001b[1;32mif\u001b[0m \u001b[0mattr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mattr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    389\u001b[0m         \u001b[1;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    390\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__dir__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mcustom_dir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_dir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Users\\David\\anaconda3\\lib\\site-packages\\torch\\nn\\modules\\module.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m    945\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mname\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mmodules\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    946\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mmodules\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 947\u001b[1;33m         raise AttributeError(\"'{}' object has no attribute '{}'\".format(\n\u001b[0m\u001b[0;32m    948\u001b[0m             type(self).__name__, name))\n\u001b[0;32m    949\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'Sequential' object has no attribute 'plot'"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%time\n",
    "# Hypermaramter tuning\n",
    "learn.unfreeze()\n",
    "learn.lr_find()\n",
    "learn.recorder.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.144758</td>\n",
       "      <td>0.276781</td>\n",
       "      <td>0.895432</td>\n",
       "      <td>11:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.fit_one_cycle(1,slice(1e-7,1e-3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Unfreezing the weights resulted in a slighly lower accuracy, but a fairly significant increase in validation loss. I expect this was overfitting, as the train loss went down while the validation loss went up. So I am going to use the previous model that was trained and tuned on 3 epochs.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interp = ClassificationInterpretation.from_learner(learn)\n",
    "interp.plot_confusion_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.show_results()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "83257"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dls.valid_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23623"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Class 1 images in the validation set\n",
    "4846+18777"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sensitivity: 0.7948609406087288\n",
      "Specificity: 0.937267330717376\n",
      "Accuracy: 0.8968615251570438\n",
      "PPV: 0.8338662403410605\n",
      "NPV: 0.9202160061904213\n"
     ]
    }
   ],
   "source": [
    "# Calculate sensitivity and specificity\n",
    "upp, low = interp.confusion_matrix()\n",
    "tn, fp = upp[0], upp[1]\n",
    "fn, tp = low[0], low[1]\n",
    "\n",
    "# Sensitivity = True Positive/(True Positive + False Negative)\n",
    "sensitivity = tp/(tp + fn)\n",
    "\n",
    "# Specificity = True Negative/(False Positive + True Negative)\n",
    "# aka Type II error\n",
    "specificity = tn/(fp + tn)\n",
    "\n",
    "# Positive Predictive Value aka Type I error\n",
    "ppv = tp/(tp+fp)\n",
    "\n",
    "# Negative Predictive Value\n",
    "npv = tn/(tn+fn)\n",
    "\n",
    "# Accuracy: sensitivity x prevalence + specificity * (1 - prevalence)\n",
    "val = dls.valid_ds.cat\n",
    "\n",
    "\n",
    "# There are 23,623 class 1 images in the valid set (which has a total of 83,257 images \n",
    "# and can be checked by using len(dls.valid_ds)).\n",
    "prevalence = 23623/83257\n",
    "accuracy = sensitivity * prevalence + specificity * (1 - prevalence)\n",
    "\n",
    "print(\"Sensitivity: {}\".format(sensitivity))\n",
    "print(\"Specificity: {}\".format(specificity))\n",
    "print(\"Accuracy: {}\".format(accuracy))\n",
    "print(\"PPV: {}\".format(ppv))\n",
    "print(\"NPV: {}\".format(npv))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "****************************\n",
    "**I am pretty happy with the final model results. While I never did get the accuracy to break 90%, the more important factor for me is a NPV of 92%. If my interpretation is correct, this model predicts false negatives at a rate of 8% (the prevailing rate for humans is closer to 20%!).**  \n",
    "****************************"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Side notes on Results Evaluation\n",
    "\n",
    "*(Note: this entire section was copied whole from [the fastai website](https://docs.fast.ai/tutorial.medical_imaging.html))* \n",
    "\n",
    "Medical models are predominantly high impact so it is important to know how good a model is at detecting a certain condition.\n",
    "\n",
    "`Accuracy` can be defined as the number of correctly predicted data points out of all the data points. However in this context we can define accuracy as the probability that the model is correct and the patient has the condition PLUS the probability that the model is correct and the patient *does not* have the condition.\n",
    "\n",
    "**Calculating Accuracy**\n",
    "\n",
    "**accuracy = sensitivity x prevalence + specificity * (1 - prevalence)**\n",
    "\n",
    "Where **prevalence** is a statistical concept referring to the number of cases of a disease that are present in a particular population at a given time. The prevalence in this case is how many patients in the valid dataset have the condition compared to the total number.\n",
    "\n",
    "There are some other key terms that need to be used when evaluating medical models:\n",
    "\n",
    "**False Positive & False Negative**\n",
    "\n",
    "* **False Positive** is an error in which a test result improperly indicates presence of a condition, such as a disease (the result is positive), when in reality it is not present\n",
    "* **False Negative** is an error in which a test result improperly indicates no presence of a condition (the result is negative), when in reality it is present  \n",
    "\n",
    "**Sensitivity & Specificity**\n",
    "\n",
    "* **Sensitivity or True Positive Rate** is where the model classifies a patient has the disease given the patient actually does have the disease. Sensitivity quantifies the avoidance of false negatives  \n",
    "\n",
    "Example: A new test was tested on 10,000 patients, if the new test has a sensitivity of 90% the test will correctly detect 9,000 (True Positive) patients but will miss 1000 (False Negative) patients that have the condition but were tested as not having the condition  \n",
    "\n",
    "* **Specificity or True Negative Rate** is where the model classifies a patient as not having the disease given the patient actually does not have the disease. Specificity quantifies the avoidance of false positives  \n",
    "\n",
    "[Understanding and using sensitivity, specificity and predictive values](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2636062/) is a great paper if you are interested in learning more about understanding sensitivity, specificity and predictive values.\n",
    "\n",
    "**PPV and NPV**\n",
    "\n",
    "Most medical testing is evaluated via PPV (Positive Predictive Value) or NPV (Negative Predictive Value).\n",
    "\n",
    "**PPV** - if the model predicts a patient has a condition what is the probability that the patient actually has the condition\n",
    "\n",
    "**NPV** - if the model predicts a patient does not have a condition what is the probability that the patient actually does not have the condition\n",
    "\n",
    "The ideal value of the PPV, with a perfect test, is 1 (100%), and the worst possible value would be zero\n",
    "\n",
    "The ideal value of the NPV, with a perfect test, is 1 (100%), and the worst possible value would be zero"
   ]
  }
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