Voiture-Bateau-Classification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1556b371",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importation des bibliotheques necessaires\n",
    "\n",
    "import pandas as pd\n",
    "from sklearn import svm\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "from skimage.transform import resize\n",
    "from skimage.io import imread\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report,accuracy_score,confusion_matrix\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "082f2056",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading... category : car\n",
      "loaded category:car successfully\n",
      "loading... category : ship\n",
      "loaded category:ship successfully\n"
     ]
    },
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>67491</th>\n",
       "      <th>67492</th>\n",
       "      <th>67493</th>\n",
       "      <th>67494</th>\n",
       "      <th>67495</th>\n",
       "      <th>67496</th>\n",
       "      <th>67497</th>\n",
       "      <th>67498</th>\n",
       "      <th>67499</th>\n",
       "      <th>Target</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.237869</td>\n",
       "      <td>0.182967</td>\n",
       "      <td>0.077085</td>\n",
       "      <td>0.229791</td>\n",
       "      <td>0.174889</td>\n",
       "      <td>0.069007</td>\n",
       "      <td>0.282092</td>\n",
       "      <td>0.227190</td>\n",
       "      <td>0.121307</td>\n",
       "      <td>0.351686</td>\n",
       "      <td>...</td>\n",
       "      <td>0.198170</td>\n",
       "      <td>0.186405</td>\n",
       "      <td>0.221699</td>\n",
       "      <td>0.144954</td>\n",
       "      <td>0.133190</td>\n",
       "      <td>0.168484</td>\n",
       "      <td>0.189895</td>\n",
       "      <td>0.178131</td>\n",
       "      <td>0.213425</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.658431</td>\n",
       "      <td>0.399608</td>\n",
       "      <td>0.203529</td>\n",
       "      <td>0.656078</td>\n",
       "      <td>0.397255</td>\n",
       "      <td>0.201176</td>\n",
       "      <td>0.651438</td>\n",
       "      <td>0.392614</td>\n",
       "      <td>0.196536</td>\n",
       "      <td>0.646797</td>\n",
       "      <td>...</td>\n",
       "      <td>0.394967</td>\n",
       "      <td>0.386536</td>\n",
       "      <td>0.343399</td>\n",
       "      <td>0.373974</td>\n",
       "      <td>0.368209</td>\n",
       "      <td>0.330824</td>\n",
       "      <td>0.389895</td>\n",
       "      <td>0.390641</td>\n",
       "      <td>0.350902</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.019608</td>\n",
       "      <td>0.105882</td>\n",
       "      <td>0.098039</td>\n",
       "      <td>0.019608</td>\n",
       "      <td>0.105882</td>\n",
       "      <td>0.098039</td>\n",
       "      <td>0.019608</td>\n",
       "      <td>0.105882</td>\n",
       "      <td>0.098039</td>\n",
       "      <td>0.019608</td>\n",
       "      <td>...</td>\n",
       "      <td>0.467908</td>\n",
       "      <td>0.427778</td>\n",
       "      <td>0.254314</td>\n",
       "      <td>0.412183</td>\n",
       "      <td>0.366039</td>\n",
       "      <td>0.198588</td>\n",
       "      <td>0.459556</td>\n",
       "      <td>0.413412</td>\n",
       "      <td>0.245961</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.219647</td>\n",
       "      <td>0.117686</td>\n",
       "      <td>0.058863</td>\n",
       "      <td>0.221451</td>\n",
       "      <td>0.119490</td>\n",
       "      <td>0.060667</td>\n",
       "      <td>0.224314</td>\n",
       "      <td>0.122353</td>\n",
       "      <td>0.063529</td>\n",
       "      <td>0.227451</td>\n",
       "      <td>...</td>\n",
       "      <td>0.078301</td>\n",
       "      <td>0.022484</td>\n",
       "      <td>0.020980</td>\n",
       "      <td>0.072810</td>\n",
       "      <td>0.020261</td>\n",
       "      <td>0.020261</td>\n",
       "      <td>0.065752</td>\n",
       "      <td>0.017908</td>\n",
       "      <td>0.017908</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.879346</td>\n",
       "      <td>0.883268</td>\n",
       "      <td>0.647974</td>\n",
       "      <td>0.879346</td>\n",
       "      <td>0.883268</td>\n",
       "      <td>0.647974</td>\n",
       "      <td>0.877386</td>\n",
       "      <td>0.881307</td>\n",
       "      <td>0.646013</td>\n",
       "      <td>0.875425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.330327</td>\n",
       "      <td>0.259739</td>\n",
       "      <td>0.251895</td>\n",
       "      <td>0.330327</td>\n",
       "      <td>0.259739</td>\n",
       "      <td>0.251895</td>\n",
       "      <td>0.330327</td>\n",
       "      <td>0.259739</td>\n",
       "      <td>0.251895</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.387294</td>\n",
       "      <td>0.319072</td>\n",
       "      <td>0.096444</td>\n",
       "      <td>0.413020</td>\n",
       "      <td>0.346444</td>\n",
       "      <td>0.122170</td>\n",
       "      <td>0.427843</td>\n",
       "      <td>0.362680</td>\n",
       "      <td>0.133072</td>\n",
       "      <td>0.426314</td>\n",
       "      <td>...</td>\n",
       "      <td>0.077386</td>\n",
       "      <td>0.061699</td>\n",
       "      <td>0.049935</td>\n",
       "      <td>0.074248</td>\n",
       "      <td>0.058562</td>\n",
       "      <td>0.046797</td>\n",
       "      <td>0.071895</td>\n",
       "      <td>0.056209</td>\n",
       "      <td>0.044444</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.260078</td>\n",
       "      <td>0.292366</td>\n",
       "      <td>0.090536</td>\n",
       "      <td>0.249569</td>\n",
       "      <td>0.281856</td>\n",
       "      <td>0.080026</td>\n",
       "      <td>0.237516</td>\n",
       "      <td>0.271307</td>\n",
       "      <td>0.066471</td>\n",
       "      <td>0.230719</td>\n",
       "      <td>...</td>\n",
       "      <td>0.187908</td>\n",
       "      <td>0.297712</td>\n",
       "      <td>0.140850</td>\n",
       "      <td>0.189686</td>\n",
       "      <td>0.299490</td>\n",
       "      <td>0.142627</td>\n",
       "      <td>0.190235</td>\n",
       "      <td>0.300039</td>\n",
       "      <td>0.143176</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.247150</td>\n",
       "      <td>0.168719</td>\n",
       "      <td>0.305974</td>\n",
       "      <td>0.247699</td>\n",
       "      <td>0.169268</td>\n",
       "      <td>0.306523</td>\n",
       "      <td>0.247974</td>\n",
       "      <td>0.169542</td>\n",
       "      <td>0.306797</td>\n",
       "      <td>0.249150</td>\n",
       "      <td>...</td>\n",
       "      <td>0.477843</td>\n",
       "      <td>0.429216</td>\n",
       "      <td>0.218105</td>\n",
       "      <td>0.476340</td>\n",
       "      <td>0.426444</td>\n",
       "      <td>0.221699</td>\n",
       "      <td>0.452810</td>\n",
       "      <td>0.402209</td>\n",
       "      <td>0.200523</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.442131</td>\n",
       "      <td>0.419778</td>\n",
       "      <td>0.405007</td>\n",
       "      <td>0.432954</td>\n",
       "      <td>0.410601</td>\n",
       "      <td>0.395830</td>\n",
       "      <td>0.423268</td>\n",
       "      <td>0.400915</td>\n",
       "      <td>0.386144</td>\n",
       "      <td>0.421503</td>\n",
       "      <td>...</td>\n",
       "      <td>0.099608</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>0.056471</td>\n",
       "      <td>0.123739</td>\n",
       "      <td>0.104131</td>\n",
       "      <td>0.080601</td>\n",
       "      <td>0.128601</td>\n",
       "      <td>0.108993</td>\n",
       "      <td>0.085464</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.489085</td>\n",
       "      <td>0.372222</td>\n",
       "      <td>0.328693</td>\n",
       "      <td>0.468301</td>\n",
       "      <td>0.356144</td>\n",
       "      <td>0.310261</td>\n",
       "      <td>0.467124</td>\n",
       "      <td>0.357320</td>\n",
       "      <td>0.310261</td>\n",
       "      <td>0.471281</td>\n",
       "      <td>...</td>\n",
       "      <td>0.161699</td>\n",
       "      <td>0.173464</td>\n",
       "      <td>0.200915</td>\n",
       "      <td>0.161699</td>\n",
       "      <td>0.173464</td>\n",
       "      <td>0.200915</td>\n",
       "      <td>0.161699</td>\n",
       "      <td>0.173464</td>\n",
       "      <td>0.200915</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.097725</td>\n",
       "      <td>0.140863</td>\n",
       "      <td>0.125176</td>\n",
       "      <td>0.131137</td>\n",
       "      <td>0.174275</td>\n",
       "      <td>0.158588</td>\n",
       "      <td>0.267190</td>\n",
       "      <td>0.308366</td>\n",
       "      <td>0.298562</td>\n",
       "      <td>0.403046</td>\n",
       "      <td>...</td>\n",
       "      <td>0.358105</td>\n",
       "      <td>0.387974</td>\n",
       "      <td>0.170784</td>\n",
       "      <td>0.415346</td>\n",
       "      <td>0.444614</td>\n",
       "      <td>0.249529</td>\n",
       "      <td>0.292052</td>\n",
       "      <td>0.323124</td>\n",
       "      <td>0.143882</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.204288</td>\n",
       "      <td>0.212131</td>\n",
       "      <td>0.129778</td>\n",
       "      <td>0.302170</td>\n",
       "      <td>0.310013</td>\n",
       "      <td>0.227660</td>\n",
       "      <td>0.254706</td>\n",
       "      <td>0.262549</td>\n",
       "      <td>0.178235</td>\n",
       "      <td>0.150183</td>\n",
       "      <td>...</td>\n",
       "      <td>0.418235</td>\n",
       "      <td>0.386405</td>\n",
       "      <td>0.105294</td>\n",
       "      <td>0.394092</td>\n",
       "      <td>0.362719</td>\n",
       "      <td>0.079281</td>\n",
       "      <td>0.367895</td>\n",
       "      <td>0.336523</td>\n",
       "      <td>0.051438</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.093255</td>\n",
       "      <td>0.131647</td>\n",
       "      <td>0.040000</td>\n",
       "      <td>0.094353</td>\n",
       "      <td>0.133294</td>\n",
       "      <td>0.040000</td>\n",
       "      <td>0.096275</td>\n",
       "      <td>0.135490</td>\n",
       "      <td>0.039869</td>\n",
       "      <td>0.098745</td>\n",
       "      <td>...</td>\n",
       "      <td>0.292484</td>\n",
       "      <td>0.249346</td>\n",
       "      <td>0.163072</td>\n",
       "      <td>0.288745</td>\n",
       "      <td>0.245608</td>\n",
       "      <td>0.159333</td>\n",
       "      <td>0.288196</td>\n",
       "      <td>0.245059</td>\n",
       "      <td>0.158784</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.152941</td>\n",
       "      <td>0.105882</td>\n",
       "      <td>0.247059</td>\n",
       "      <td>0.152941</td>\n",
       "      <td>0.105882</td>\n",
       "      <td>0.247059</td>\n",
       "      <td>0.154902</td>\n",
       "      <td>0.107843</td>\n",
       "      <td>0.249020</td>\n",
       "      <td>0.158039</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014379</td>\n",
       "      <td>0.014379</td>\n",
       "      <td>0.018301</td>\n",
       "      <td>0.011516</td>\n",
       "      <td>0.011516</td>\n",
       "      <td>0.019359</td>\n",
       "      <td>0.009712</td>\n",
       "      <td>0.009712</td>\n",
       "      <td>0.017556</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.894118</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.164706</td>\n",
       "      <td>0.894118</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.164706</td>\n",
       "      <td>0.892614</td>\n",
       "      <td>0.798497</td>\n",
       "      <td>0.163203</td>\n",
       "      <td>0.891111</td>\n",
       "      <td>...</td>\n",
       "      <td>0.089150</td>\n",
       "      <td>0.016144</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.093464</td>\n",
       "      <td>0.022235</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.098170</td>\n",
       "      <td>0.027490</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.222444</td>\n",
       "      <td>0.061346</td>\n",
       "      <td>0.053464</td>\n",
       "      <td>0.218288</td>\n",
       "      <td>0.065503</td>\n",
       "      <td>0.055817</td>\n",
       "      <td>0.213203</td>\n",
       "      <td>0.073922</td>\n",
       "      <td>0.059412</td>\n",
       "      <td>0.207216</td>\n",
       "      <td>...</td>\n",
       "      <td>0.884837</td>\n",
       "      <td>0.551961</td>\n",
       "      <td>0.119477</td>\n",
       "      <td>0.864039</td>\n",
       "      <td>0.531621</td>\n",
       "      <td>0.116301</td>\n",
       "      <td>0.851725</td>\n",
       "      <td>0.519307</td>\n",
       "      <td>0.109948</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.802275</td>\n",
       "      <td>0.614954</td>\n",
       "      <td>0.287373</td>\n",
       "      <td>0.805725</td>\n",
       "      <td>0.618405</td>\n",
       "      <td>0.290824</td>\n",
       "      <td>0.808824</td>\n",
       "      <td>0.623922</td>\n",
       "      <td>0.299804</td>\n",
       "      <td>0.810745</td>\n",
       "      <td>...</td>\n",
       "      <td>0.791111</td>\n",
       "      <td>0.664706</td>\n",
       "      <td>0.341046</td>\n",
       "      <td>0.789150</td>\n",
       "      <td>0.662745</td>\n",
       "      <td>0.339085</td>\n",
       "      <td>0.789150</td>\n",
       "      <td>0.662745</td>\n",
       "      <td>0.339085</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.644052</td>\n",
       "      <td>0.416510</td>\n",
       "      <td>0.130510</td>\n",
       "      <td>0.644052</td>\n",
       "      <td>0.415961</td>\n",
       "      <td>0.131608</td>\n",
       "      <td>0.647516</td>\n",
       "      <td>0.413725</td>\n",
       "      <td>0.140588</td>\n",
       "      <td>0.651255</td>\n",
       "      <td>...</td>\n",
       "      <td>0.035752</td>\n",
       "      <td>0.012222</td>\n",
       "      <td>0.027908</td>\n",
       "      <td>0.035294</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.027451</td>\n",
       "      <td>0.035294</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.027451</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.039739</td>\n",
       "      <td>0.067190</td>\n",
       "      <td>0.035817</td>\n",
       "      <td>0.039739</td>\n",
       "      <td>0.067190</td>\n",
       "      <td>0.035817</td>\n",
       "      <td>0.039739</td>\n",
       "      <td>0.069150</td>\n",
       "      <td>0.031895</td>\n",
       "      <td>0.039739</td>\n",
       "      <td>...</td>\n",
       "      <td>0.187124</td>\n",
       "      <td>0.268562</td>\n",
       "      <td>0.045490</td>\n",
       "      <td>0.183111</td>\n",
       "      <td>0.264183</td>\n",
       "      <td>0.041294</td>\n",
       "      <td>0.182013</td>\n",
       "      <td>0.264183</td>\n",
       "      <td>0.040745</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.187569</td>\n",
       "      <td>0.074026</td>\n",
       "      <td>0.019908</td>\n",
       "      <td>0.203961</td>\n",
       "      <td>0.091516</td>\n",
       "      <td>0.035046</td>\n",
       "      <td>0.217059</td>\n",
       "      <td>0.106209</td>\n",
       "      <td>0.054444</td>\n",
       "      <td>0.214510</td>\n",
       "      <td>...</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.047059</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.047059</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.047059</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.581359</td>\n",
       "      <td>0.597046</td>\n",
       "      <td>0.608627</td>\n",
       "      <td>0.573046</td>\n",
       "      <td>0.588732</td>\n",
       "      <td>0.599216</td>\n",
       "      <td>0.560915</td>\n",
       "      <td>0.576601</td>\n",
       "      <td>0.583529</td>\n",
       "      <td>0.552941</td>\n",
       "      <td>...</td>\n",
       "      <td>0.273529</td>\n",
       "      <td>0.260392</td>\n",
       "      <td>0.202941</td>\n",
       "      <td>0.287948</td>\n",
       "      <td>0.274261</td>\n",
       "      <td>0.217359</td>\n",
       "      <td>0.296261</td>\n",
       "      <td>0.284222</td>\n",
       "      <td>0.225673</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.487608</td>\n",
       "      <td>0.463255</td>\n",
       "      <td>0.379451</td>\n",
       "      <td>0.519922</td>\n",
       "      <td>0.496118</td>\n",
       "      <td>0.410667</td>\n",
       "      <td>0.536601</td>\n",
       "      <td>0.512614</td>\n",
       "      <td>0.427712</td>\n",
       "      <td>0.532693</td>\n",
       "      <td>...</td>\n",
       "      <td>0.076340</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.076340</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.076340</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.650993</td>\n",
       "      <td>0.639229</td>\n",
       "      <td>0.580405</td>\n",
       "      <td>0.650288</td>\n",
       "      <td>0.638523</td>\n",
       "      <td>0.579699</td>\n",
       "      <td>0.647843</td>\n",
       "      <td>0.636078</td>\n",
       "      <td>0.577255</td>\n",
       "      <td>0.644497</td>\n",
       "      <td>...</td>\n",
       "      <td>0.469869</td>\n",
       "      <td>0.430654</td>\n",
       "      <td>0.324771</td>\n",
       "      <td>0.476314</td>\n",
       "      <td>0.437098</td>\n",
       "      <td>0.331216</td>\n",
       "      <td>0.482275</td>\n",
       "      <td>0.443059</td>\n",
       "      <td>0.337176</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>...</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0.007843</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.452536</td>\n",
       "      <td>0.368536</td>\n",
       "      <td>0.160876</td>\n",
       "      <td>0.407752</td>\n",
       "      <td>0.324850</td>\n",
       "      <td>0.123778</td>\n",
       "      <td>0.386797</td>\n",
       "      <td>0.303529</td>\n",
       "      <td>0.100719</td>\n",
       "      <td>0.383647</td>\n",
       "      <td>...</td>\n",
       "      <td>0.093464</td>\n",
       "      <td>0.043725</td>\n",
       "      <td>0.003660</td>\n",
       "      <td>0.094627</td>\n",
       "      <td>0.045190</td>\n",
       "      <td>0.005948</td>\n",
       "      <td>0.066627</td>\n",
       "      <td>0.020797</td>\n",
       "      <td>0.003203</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.314641</td>\n",
       "      <td>0.314641</td>\n",
       "      <td>0.322484</td>\n",
       "      <td>0.314641</td>\n",
       "      <td>0.314641</td>\n",
       "      <td>0.322484</td>\n",
       "      <td>0.314641</td>\n",
       "      <td>0.314641</td>\n",
       "      <td>0.322484</td>\n",
       "      <td>0.314641</td>\n",
       "      <td>...</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.003922</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.003922</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.011765</td>\n",
       "      <td>0.003922</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.006013</td>\n",
       "      <td>0.006013</td>\n",
       "      <td>0.006013</td>\n",
       "      <td>0.006013</td>\n",
       "      <td>0.006013</td>\n",
       "      <td>0.006013</td>\n",
       "      <td>0.007386</td>\n",
       "      <td>0.007386</td>\n",
       "      <td>0.007386</td>\n",
       "      <td>0.009582</td>\n",
       "      <td>...</td>\n",
       "      <td>0.518105</td>\n",
       "      <td>0.384771</td>\n",
       "      <td>0.235752</td>\n",
       "      <td>0.513464</td>\n",
       "      <td>0.380131</td>\n",
       "      <td>0.231111</td>\n",
       "      <td>0.511111</td>\n",
       "      <td>0.377778</td>\n",
       "      <td>0.228758</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.657516</td>\n",
       "      <td>0.453595</td>\n",
       "      <td>0.116340</td>\n",
       "      <td>0.658039</td>\n",
       "      <td>0.454118</td>\n",
       "      <td>0.116863</td>\n",
       "      <td>0.662222</td>\n",
       "      <td>0.458301</td>\n",
       "      <td>0.121046</td>\n",
       "      <td>0.669281</td>\n",
       "      <td>...</td>\n",
       "      <td>0.077320</td>\n",
       "      <td>0.006078</td>\n",
       "      <td>0.001503</td>\n",
       "      <td>0.081294</td>\n",
       "      <td>0.010471</td>\n",
       "      <td>0.003804</td>\n",
       "      <td>0.081791</td>\n",
       "      <td>0.011020</td>\n",
       "      <td>0.004092</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.174889</td>\n",
       "      <td>0.218026</td>\n",
       "      <td>0.163124</td>\n",
       "      <td>0.177686</td>\n",
       "      <td>0.220824</td>\n",
       "      <td>0.165922</td>\n",
       "      <td>0.200065</td>\n",
       "      <td>0.243203</td>\n",
       "      <td>0.188301</td>\n",
       "      <td>0.213961</td>\n",
       "      <td>...</td>\n",
       "      <td>0.324837</td>\n",
       "      <td>0.263399</td>\n",
       "      <td>0.161438</td>\n",
       "      <td>0.293882</td>\n",
       "      <td>0.236627</td>\n",
       "      <td>0.134667</td>\n",
       "      <td>0.290013</td>\n",
       "      <td>0.233281</td>\n",
       "      <td>0.131320</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.661882</td>\n",
       "      <td>0.599137</td>\n",
       "      <td>0.405150</td>\n",
       "      <td>0.674745</td>\n",
       "      <td>0.612000</td>\n",
       "      <td>0.418013</td>\n",
       "      <td>0.725425</td>\n",
       "      <td>0.666601</td>\n",
       "      <td>0.479542</td>\n",
       "      <td>0.763163</td>\n",
       "      <td>...</td>\n",
       "      <td>0.671438</td>\n",
       "      <td>0.538105</td>\n",
       "      <td>0.389085</td>\n",
       "      <td>0.687503</td>\n",
       "      <td>0.554170</td>\n",
       "      <td>0.405150</td>\n",
       "      <td>0.700680</td>\n",
       "      <td>0.567346</td>\n",
       "      <td>0.418327</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.679647</td>\n",
       "      <td>0.691412</td>\n",
       "      <td>0.813163</td>\n",
       "      <td>0.681451</td>\n",
       "      <td>0.693216</td>\n",
       "      <td>0.816065</td>\n",
       "      <td>0.682810</td>\n",
       "      <td>0.694575</td>\n",
       "      <td>0.824902</td>\n",
       "      <td>0.684444</td>\n",
       "      <td>...</td>\n",
       "      <td>0.401438</td>\n",
       "      <td>0.403399</td>\n",
       "      <td>0.530850</td>\n",
       "      <td>0.364144</td>\n",
       "      <td>0.364144</td>\n",
       "      <td>0.497477</td>\n",
       "      <td>0.308379</td>\n",
       "      <td>0.308379</td>\n",
       "      <td>0.441712</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.299869</td>\n",
       "      <td>0.503791</td>\n",
       "      <td>0.727320</td>\n",
       "      <td>0.299869</td>\n",
       "      <td>0.503791</td>\n",
       "      <td>0.727320</td>\n",
       "      <td>0.299869</td>\n",
       "      <td>0.505752</td>\n",
       "      <td>0.723399</td>\n",
       "      <td>0.301046</td>\n",
       "      <td>...</td>\n",
       "      <td>0.445098</td>\n",
       "      <td>0.521438</td>\n",
       "      <td>0.582092</td>\n",
       "      <td>0.567595</td>\n",
       "      <td>0.643935</td>\n",
       "      <td>0.704588</td>\n",
       "      <td>0.335203</td>\n",
       "      <td>0.411542</td>\n",
       "      <td>0.472196</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.030850</td>\n",
       "      <td>0.175948</td>\n",
       "      <td>0.442614</td>\n",
       "      <td>0.033203</td>\n",
       "      <td>0.178301</td>\n",
       "      <td>0.444967</td>\n",
       "      <td>0.034837</td>\n",
       "      <td>0.182941</td>\n",
       "      <td>0.448105</td>\n",
       "      <td>0.036471</td>\n",
       "      <td>...</td>\n",
       "      <td>0.080980</td>\n",
       "      <td>0.100588</td>\n",
       "      <td>0.089412</td>\n",
       "      <td>0.079373</td>\n",
       "      <td>0.095974</td>\n",
       "      <td>0.089307</td>\n",
       "      <td>0.071059</td>\n",
       "      <td>0.087660</td>\n",
       "      <td>0.080993</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.436209</td>\n",
       "      <td>0.549935</td>\n",
       "      <td>0.714641</td>\n",
       "      <td>0.436209</td>\n",
       "      <td>0.549935</td>\n",
       "      <td>0.714641</td>\n",
       "      <td>0.436209</td>\n",
       "      <td>0.549935</td>\n",
       "      <td>0.714641</td>\n",
       "      <td>0.436209</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036471</td>\n",
       "      <td>0.195294</td>\n",
       "      <td>0.361961</td>\n",
       "      <td>0.003569</td>\n",
       "      <td>0.155608</td>\n",
       "      <td>0.324235</td>\n",
       "      <td>0.002863</td>\n",
       "      <td>0.153098</td>\n",
       "      <td>0.321725</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.173072</td>\n",
       "      <td>0.464444</td>\n",
       "      <td>0.688889</td>\n",
       "      <td>0.177778</td>\n",
       "      <td>0.469150</td>\n",
       "      <td>0.693595</td>\n",
       "      <td>0.187059</td>\n",
       "      <td>0.473922</td>\n",
       "      <td>0.699869</td>\n",
       "      <td>0.194889</td>\n",
       "      <td>...</td>\n",
       "      <td>0.188039</td>\n",
       "      <td>0.279608</td>\n",
       "      <td>0.479150</td>\n",
       "      <td>0.109268</td>\n",
       "      <td>0.203190</td>\n",
       "      <td>0.408824</td>\n",
       "      <td>0.049111</td>\n",
       "      <td>0.144993</td>\n",
       "      <td>0.355882</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.571333</td>\n",
       "      <td>0.673294</td>\n",
       "      <td>0.779176</td>\n",
       "      <td>0.569529</td>\n",
       "      <td>0.671490</td>\n",
       "      <td>0.777373</td>\n",
       "      <td>0.568627</td>\n",
       "      <td>0.670588</td>\n",
       "      <td>0.776471</td>\n",
       "      <td>0.569529</td>\n",
       "      <td>...</td>\n",
       "      <td>0.071373</td>\n",
       "      <td>0.079216</td>\n",
       "      <td>0.165490</td>\n",
       "      <td>0.058484</td>\n",
       "      <td>0.066327</td>\n",
       "      <td>0.156523</td>\n",
       "      <td>0.060680</td>\n",
       "      <td>0.068523</td>\n",
       "      <td>0.158719</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.525490</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.764706</td>\n",
       "      <td>0.525490</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.764706</td>\n",
       "      <td>0.525490</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.764706</td>\n",
       "      <td>0.526667</td>\n",
       "      <td>...</td>\n",
       "      <td>0.279346</td>\n",
       "      <td>0.330327</td>\n",
       "      <td>0.463660</td>\n",
       "      <td>0.273778</td>\n",
       "      <td>0.324758</td>\n",
       "      <td>0.458092</td>\n",
       "      <td>0.272052</td>\n",
       "      <td>0.323033</td>\n",
       "      <td>0.456366</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.117346</td>\n",
       "      <td>0.415386</td>\n",
       "      <td>0.642837</td>\n",
       "      <td>0.108484</td>\n",
       "      <td>0.406523</td>\n",
       "      <td>0.633974</td>\n",
       "      <td>0.092745</td>\n",
       "      <td>0.396667</td>\n",
       "      <td>0.622157</td>\n",
       "      <td>0.080261</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063922</td>\n",
       "      <td>0.133595</td>\n",
       "      <td>0.269346</td>\n",
       "      <td>0.054065</td>\n",
       "      <td>0.116810</td>\n",
       "      <td>0.250144</td>\n",
       "      <td>0.064418</td>\n",
       "      <td>0.127163</td>\n",
       "      <td>0.260497</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.096732</td>\n",
       "      <td>0.433203</td>\n",
       "      <td>0.617346</td>\n",
       "      <td>0.087320</td>\n",
       "      <td>0.433203</td>\n",
       "      <td>0.617895</td>\n",
       "      <td>0.071765</td>\n",
       "      <td>0.433660</td>\n",
       "      <td>0.629477</td>\n",
       "      <td>0.055582</td>\n",
       "      <td>...</td>\n",
       "      <td>0.024183</td>\n",
       "      <td>0.114837</td>\n",
       "      <td>0.200065</td>\n",
       "      <td>0.034562</td>\n",
       "      <td>0.117830</td>\n",
       "      <td>0.201464</td>\n",
       "      <td>0.043817</td>\n",
       "      <td>0.127085</td>\n",
       "      <td>0.209621</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.580484</td>\n",
       "      <td>0.702052</td>\n",
       "      <td>0.823438</td>\n",
       "      <td>0.573974</td>\n",
       "      <td>0.695542</td>\n",
       "      <td>0.815830</td>\n",
       "      <td>0.565294</td>\n",
       "      <td>0.686863</td>\n",
       "      <td>0.807516</td>\n",
       "      <td>0.558967</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152810</td>\n",
       "      <td>0.172876</td>\n",
       "      <td>0.324902</td>\n",
       "      <td>0.174641</td>\n",
       "      <td>0.194248</td>\n",
       "      <td>0.353464</td>\n",
       "      <td>0.200523</td>\n",
       "      <td>0.220131</td>\n",
       "      <td>0.384052</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.189673</td>\n",
       "      <td>0.448497</td>\n",
       "      <td>0.636732</td>\n",
       "      <td>0.187320</td>\n",
       "      <td>0.446144</td>\n",
       "      <td>0.634379</td>\n",
       "      <td>0.184641</td>\n",
       "      <td>0.443464</td>\n",
       "      <td>0.631699</td>\n",
       "      <td>0.182863</td>\n",
       "      <td>...</td>\n",
       "      <td>0.142614</td>\n",
       "      <td>0.257516</td>\n",
       "      <td>0.365229</td>\n",
       "      <td>0.147020</td>\n",
       "      <td>0.262745</td>\n",
       "      <td>0.373190</td>\n",
       "      <td>0.147725</td>\n",
       "      <td>0.265098</td>\n",
       "      <td>0.374993</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.639281</td>\n",
       "      <td>0.606078</td>\n",
       "      <td>0.563856</td>\n",
       "      <td>0.613791</td>\n",
       "      <td>0.580588</td>\n",
       "      <td>0.538366</td>\n",
       "      <td>0.608431</td>\n",
       "      <td>0.572222</td>\n",
       "      <td>0.531503</td>\n",
       "      <td>0.632641</td>\n",
       "      <td>...</td>\n",
       "      <td>0.142418</td>\n",
       "      <td>0.193399</td>\n",
       "      <td>0.224771</td>\n",
       "      <td>0.117739</td>\n",
       "      <td>0.168719</td>\n",
       "      <td>0.200092</td>\n",
       "      <td>0.124719</td>\n",
       "      <td>0.175699</td>\n",
       "      <td>0.207072</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.255072</td>\n",
       "      <td>0.306497</td>\n",
       "      <td>0.551856</td>\n",
       "      <td>0.270993</td>\n",
       "      <td>0.323516</td>\n",
       "      <td>0.564170</td>\n",
       "      <td>0.299477</td>\n",
       "      <td>0.351634</td>\n",
       "      <td>0.589477</td>\n",
       "      <td>0.327608</td>\n",
       "      <td>...</td>\n",
       "      <td>0.043595</td>\n",
       "      <td>0.092614</td>\n",
       "      <td>0.336797</td>\n",
       "      <td>0.031869</td>\n",
       "      <td>0.074458</td>\n",
       "      <td>0.317595</td>\n",
       "      <td>0.017438</td>\n",
       "      <td>0.058928</td>\n",
       "      <td>0.302065</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.435386</td>\n",
       "      <td>0.517739</td>\n",
       "      <td>0.843229</td>\n",
       "      <td>0.435935</td>\n",
       "      <td>0.518288</td>\n",
       "      <td>0.843778</td>\n",
       "      <td>0.438170</td>\n",
       "      <td>0.520523</td>\n",
       "      <td>0.846013</td>\n",
       "      <td>0.441307</td>\n",
       "      <td>...</td>\n",
       "      <td>0.165817</td>\n",
       "      <td>0.208954</td>\n",
       "      <td>0.491307</td>\n",
       "      <td>0.157516</td>\n",
       "      <td>0.196732</td>\n",
       "      <td>0.479085</td>\n",
       "      <td>0.171634</td>\n",
       "      <td>0.210850</td>\n",
       "      <td>0.493203</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0.823529</td>\n",
       "      <td>0.823529</td>\n",
       "      <td>0.854902</td>\n",
       "      <td>0.823529</td>\n",
       "      <td>0.823529</td>\n",
       "      <td>0.854902</td>\n",
       "      <td>0.823529</td>\n",
       "      <td>0.823529</td>\n",
       "      <td>0.854902</td>\n",
       "      <td>0.823529</td>\n",
       "      <td>...</td>\n",
       "      <td>0.142941</td>\n",
       "      <td>0.193922</td>\n",
       "      <td>0.260588</td>\n",
       "      <td>0.140248</td>\n",
       "      <td>0.191229</td>\n",
       "      <td>0.257895</td>\n",
       "      <td>0.139699</td>\n",
       "      <td>0.190680</td>\n",
       "      <td>0.257346</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.385712</td>\n",
       "      <td>0.471987</td>\n",
       "      <td>0.769935</td>\n",
       "      <td>0.388614</td>\n",
       "      <td>0.474889</td>\n",
       "      <td>0.772288</td>\n",
       "      <td>0.393987</td>\n",
       "      <td>0.480261</td>\n",
       "      <td>0.775882</td>\n",
       "      <td>0.399085</td>\n",
       "      <td>...</td>\n",
       "      <td>0.481569</td>\n",
       "      <td>0.314575</td>\n",
       "      <td>0.293791</td>\n",
       "      <td>0.476797</td>\n",
       "      <td>0.313268</td>\n",
       "      <td>0.292484</td>\n",
       "      <td>0.478758</td>\n",
       "      <td>0.315229</td>\n",
       "      <td>0.294444</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.472941</td>\n",
       "      <td>0.527843</td>\n",
       "      <td>0.774902</td>\n",
       "      <td>0.470588</td>\n",
       "      <td>0.525490</td>\n",
       "      <td>0.772549</td>\n",
       "      <td>0.467908</td>\n",
       "      <td>0.522810</td>\n",
       "      <td>0.769869</td>\n",
       "      <td>0.466131</td>\n",
       "      <td>...</td>\n",
       "      <td>0.589150</td>\n",
       "      <td>0.598954</td>\n",
       "      <td>0.653856</td>\n",
       "      <td>0.559307</td>\n",
       "      <td>0.571072</td>\n",
       "      <td>0.632248</td>\n",
       "      <td>0.449425</td>\n",
       "      <td>0.461190</td>\n",
       "      <td>0.527072</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.332549</td>\n",
       "      <td>0.477647</td>\n",
       "      <td>0.752157</td>\n",
       "      <td>0.334902</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.754510</td>\n",
       "      <td>0.341503</td>\n",
       "      <td>0.480719</td>\n",
       "      <td>0.757190</td>\n",
       "      <td>0.348105</td>\n",
       "      <td>...</td>\n",
       "      <td>0.310327</td>\n",
       "      <td>0.376993</td>\n",
       "      <td>0.557386</td>\n",
       "      <td>0.341203</td>\n",
       "      <td>0.407869</td>\n",
       "      <td>0.588261</td>\n",
       "      <td>0.360340</td>\n",
       "      <td>0.427007</td>\n",
       "      <td>0.607399</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>0.034771</td>\n",
       "      <td>0.266144</td>\n",
       "      <td>0.626928</td>\n",
       "      <td>0.044183</td>\n",
       "      <td>0.275556</td>\n",
       "      <td>0.636340</td>\n",
       "      <td>0.062614</td>\n",
       "      <td>0.288105</td>\n",
       "      <td>0.650850</td>\n",
       "      <td>0.082222</td>\n",
       "      <td>...</td>\n",
       "      <td>0.034118</td>\n",
       "      <td>0.057647</td>\n",
       "      <td>0.229281</td>\n",
       "      <td>0.043660</td>\n",
       "      <td>0.061163</td>\n",
       "      <td>0.232183</td>\n",
       "      <td>0.025621</td>\n",
       "      <td>0.044928</td>\n",
       "      <td>0.210536</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>0.000915</td>\n",
       "      <td>0.363137</td>\n",
       "      <td>0.599647</td>\n",
       "      <td>0.000915</td>\n",
       "      <td>0.360784</td>\n",
       "      <td>0.599098</td>\n",
       "      <td>0.000915</td>\n",
       "      <td>0.356732</td>\n",
       "      <td>0.596405</td>\n",
       "      <td>0.001464</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018562</td>\n",
       "      <td>0.237712</td>\n",
       "      <td>0.467255</td>\n",
       "      <td>0.020248</td>\n",
       "      <td>0.239216</td>\n",
       "      <td>0.468758</td>\n",
       "      <td>0.019699</td>\n",
       "      <td>0.239216</td>\n",
       "      <td>0.468758</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.015503</td>\n",
       "      <td>0.195895</td>\n",
       "      <td>0.290013</td>\n",
       "      <td>0.030876</td>\n",
       "      <td>0.211268</td>\n",
       "      <td>0.305386</td>\n",
       "      <td>0.019281</td>\n",
       "      <td>0.188824</td>\n",
       "      <td>0.280980</td>\n",
       "      <td>0.016510</td>\n",
       "      <td>...</td>\n",
       "      <td>0.473268</td>\n",
       "      <td>0.651699</td>\n",
       "      <td>0.737974</td>\n",
       "      <td>0.559895</td>\n",
       "      <td>0.736366</td>\n",
       "      <td>0.818719</td>\n",
       "      <td>0.502170</td>\n",
       "      <td>0.678641</td>\n",
       "      <td>0.760993</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>0.338641</td>\n",
       "      <td>0.515111</td>\n",
       "      <td>0.679817</td>\n",
       "      <td>0.328131</td>\n",
       "      <td>0.504601</td>\n",
       "      <td>0.669307</td>\n",
       "      <td>0.297320</td>\n",
       "      <td>0.469869</td>\n",
       "      <td>0.634575</td>\n",
       "      <td>0.287569</td>\n",
       "      <td>...</td>\n",
       "      <td>0.443203</td>\n",
       "      <td>0.603987</td>\n",
       "      <td>0.674575</td>\n",
       "      <td>0.483634</td>\n",
       "      <td>0.644418</td>\n",
       "      <td>0.715007</td>\n",
       "      <td>0.532732</td>\n",
       "      <td>0.693516</td>\n",
       "      <td>0.764105</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>0.192157</td>\n",
       "      <td>0.196078</td>\n",
       "      <td>0.274510</td>\n",
       "      <td>0.199216</td>\n",
       "      <td>0.203137</td>\n",
       "      <td>0.281569</td>\n",
       "      <td>0.214052</td>\n",
       "      <td>0.217974</td>\n",
       "      <td>0.296405</td>\n",
       "      <td>0.229791</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010261</td>\n",
       "      <td>0.088235</td>\n",
       "      <td>0.098039</td>\n",
       "      <td>0.003386</td>\n",
       "      <td>0.085098</td>\n",
       "      <td>0.089020</td>\n",
       "      <td>0.000484</td>\n",
       "      <td>0.082745</td>\n",
       "      <td>0.086667</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>0.233856</td>\n",
       "      <td>0.324052</td>\n",
       "      <td>0.484837</td>\n",
       "      <td>0.243268</td>\n",
       "      <td>0.333464</td>\n",
       "      <td>0.494248</td>\n",
       "      <td>0.259739</td>\n",
       "      <td>0.349935</td>\n",
       "      <td>0.510719</td>\n",
       "      <td>0.278288</td>\n",
       "      <td>...</td>\n",
       "      <td>0.122288</td>\n",
       "      <td>0.126209</td>\n",
       "      <td>0.134052</td>\n",
       "      <td>0.120967</td>\n",
       "      <td>0.124889</td>\n",
       "      <td>0.132732</td>\n",
       "      <td>0.047085</td>\n",
       "      <td>0.051007</td>\n",
       "      <td>0.058850</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>0.333948</td>\n",
       "      <td>0.631987</td>\n",
       "      <td>0.765320</td>\n",
       "      <td>0.332144</td>\n",
       "      <td>0.630183</td>\n",
       "      <td>0.763516</td>\n",
       "      <td>0.330784</td>\n",
       "      <td>0.628824</td>\n",
       "      <td>0.762157</td>\n",
       "      <td>0.329425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.137712</td>\n",
       "      <td>0.328039</td>\n",
       "      <td>0.495752</td>\n",
       "      <td>0.156013</td>\n",
       "      <td>0.346340</td>\n",
       "      <td>0.514052</td>\n",
       "      <td>0.165817</td>\n",
       "      <td>0.356144</td>\n",
       "      <td>0.523856</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.117137</td>\n",
       "      <td>0.314784</td>\n",
       "      <td>0.559752</td>\n",
       "      <td>0.130549</td>\n",
       "      <td>0.330549</td>\n",
       "      <td>0.568458</td>\n",
       "      <td>0.146928</td>\n",
       "      <td>0.345098</td>\n",
       "      <td>0.580523</td>\n",
       "      <td>0.155621</td>\n",
       "      <td>...</td>\n",
       "      <td>0.214641</td>\n",
       "      <td>0.286275</td>\n",
       "      <td>0.388824</td>\n",
       "      <td>0.186745</td>\n",
       "      <td>0.263895</td>\n",
       "      <td>0.361020</td>\n",
       "      <td>0.191608</td>\n",
       "      <td>0.269856</td>\n",
       "      <td>0.366980</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>0.382706</td>\n",
       "      <td>0.512719</td>\n",
       "      <td>0.673203</td>\n",
       "      <td>0.385608</td>\n",
       "      <td>0.519229</td>\n",
       "      <td>0.677908</td>\n",
       "      <td>0.388562</td>\n",
       "      <td>0.524902</td>\n",
       "      <td>0.678301</td>\n",
       "      <td>0.383281</td>\n",
       "      <td>...</td>\n",
       "      <td>0.214837</td>\n",
       "      <td>0.277451</td>\n",
       "      <td>0.385752</td>\n",
       "      <td>0.279882</td>\n",
       "      <td>0.350732</td>\n",
       "      <td>0.463895</td>\n",
       "      <td>0.267882</td>\n",
       "      <td>0.343438</td>\n",
       "      <td>0.459660</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.016601</td>\n",
       "      <td>0.263660</td>\n",
       "      <td>0.475425</td>\n",
       "      <td>0.016601</td>\n",
       "      <td>0.263660</td>\n",
       "      <td>0.475425</td>\n",
       "      <td>0.017059</td>\n",
       "      <td>0.264118</td>\n",
       "      <td>0.475882</td>\n",
       "      <td>0.018418</td>\n",
       "      <td>...</td>\n",
       "      <td>0.076732</td>\n",
       "      <td>0.085948</td>\n",
       "      <td>0.179608</td>\n",
       "      <td>0.072654</td>\n",
       "      <td>0.085948</td>\n",
       "      <td>0.174327</td>\n",
       "      <td>0.076261</td>\n",
       "      <td>0.094967</td>\n",
       "      <td>0.181542</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>0.765490</td>\n",
       "      <td>0.804706</td>\n",
       "      <td>0.840000</td>\n",
       "      <td>0.770196</td>\n",
       "      <td>0.809412</td>\n",
       "      <td>0.844706</td>\n",
       "      <td>0.776471</td>\n",
       "      <td>0.815686</td>\n",
       "      <td>0.850980</td>\n",
       "      <td>0.780118</td>\n",
       "      <td>...</td>\n",
       "      <td>0.301830</td>\n",
       "      <td>0.305752</td>\n",
       "      <td>0.388105</td>\n",
       "      <td>0.286301</td>\n",
       "      <td>0.290222</td>\n",
       "      <td>0.372575</td>\n",
       "      <td>0.257595</td>\n",
       "      <td>0.261516</td>\n",
       "      <td>0.343869</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>0.197255</td>\n",
       "      <td>0.456993</td>\n",
       "      <td>0.660915</td>\n",
       "      <td>0.197255</td>\n",
       "      <td>0.456993</td>\n",
       "      <td>0.660915</td>\n",
       "      <td>0.202680</td>\n",
       "      <td>0.457451</td>\n",
       "      <td>0.662876</td>\n",
       "      <td>0.209281</td>\n",
       "      <td>...</td>\n",
       "      <td>0.238301</td>\n",
       "      <td>0.383399</td>\n",
       "      <td>0.555948</td>\n",
       "      <td>0.244026</td>\n",
       "      <td>0.389673</td>\n",
       "      <td>0.561948</td>\n",
       "      <td>0.247634</td>\n",
       "      <td>0.394379</td>\n",
       "      <td>0.566105</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>60 rows × 67501 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           0         1         2         3         4         5         6  \\\n",
       "0   0.237869  0.182967  0.077085  0.229791  0.174889  0.069007  0.282092   \n",
       "1   0.658431  0.399608  0.203529  0.656078  0.397255  0.201176  0.651438   \n",
       "2   0.019608  0.105882  0.098039  0.019608  0.105882  0.098039  0.019608   \n",
       "3   0.219647  0.117686  0.058863  0.221451  0.119490  0.060667  0.224314   \n",
       "4   0.879346  0.883268  0.647974  0.879346  0.883268  0.647974  0.877386   \n",
       "5   0.387294  0.319072  0.096444  0.413020  0.346444  0.122170  0.427843   \n",
       "6   0.260078  0.292366  0.090536  0.249569  0.281856  0.080026  0.237516   \n",
       "7   0.247150  0.168719  0.305974  0.247699  0.169268  0.306523  0.247974   \n",
       "8   0.442131  0.419778  0.405007  0.432954  0.410601  0.395830  0.423268   \n",
       "9   0.489085  0.372222  0.328693  0.468301  0.356144  0.310261  0.467124   \n",
       "10  0.097725  0.140863  0.125176  0.131137  0.174275  0.158588  0.267190   \n",
       "11  0.204288  0.212131  0.129778  0.302170  0.310013  0.227660  0.254706   \n",
       "12  0.093255  0.131647  0.040000  0.094353  0.133294  0.040000  0.096275   \n",
       "13  0.152941  0.105882  0.247059  0.152941  0.105882  0.247059  0.154902   \n",
       "14  0.894118  0.800000  0.164706  0.894118  0.800000  0.164706  0.892614   \n",
       "15  0.222444  0.061346  0.053464  0.218288  0.065503  0.055817  0.213203   \n",
       "16  0.802275  0.614954  0.287373  0.805725  0.618405  0.290824  0.808824   \n",
       "17  0.644052  0.416510  0.130510  0.644052  0.415961  0.131608  0.647516   \n",
       "18  0.039739  0.067190  0.035817  0.039739  0.067190  0.035817  0.039739   \n",
       "19  0.187569  0.074026  0.019908  0.203961  0.091516  0.035046  0.217059   \n",
       "20  0.581359  0.597046  0.608627  0.573046  0.588732  0.599216  0.560915   \n",
       "21  0.487608  0.463255  0.379451  0.519922  0.496118  0.410667  0.536601   \n",
       "22  0.650993  0.639229  0.580405  0.650288  0.638523  0.579699  0.647843   \n",
       "23  0.007843  0.007843  0.007843  0.007843  0.007843  0.007843  0.007843   \n",
       "24  0.452536  0.368536  0.160876  0.407752  0.324850  0.123778  0.386797   \n",
       "25  0.314641  0.314641  0.322484  0.314641  0.314641  0.322484  0.314641   \n",
       "26  0.006013  0.006013  0.006013  0.006013  0.006013  0.006013  0.007386   \n",
       "27  0.657516  0.453595  0.116340  0.658039  0.454118  0.116863  0.662222   \n",
       "28  0.174889  0.218026  0.163124  0.177686  0.220824  0.165922  0.200065   \n",
       "29  0.661882  0.599137  0.405150  0.674745  0.612000  0.418013  0.725425   \n",
       "30  0.679647  0.691412  0.813163  0.681451  0.693216  0.816065  0.682810   \n",
       "31  0.299869  0.503791  0.727320  0.299869  0.503791  0.727320  0.299869   \n",
       "32  0.030850  0.175948  0.442614  0.033203  0.178301  0.444967  0.034837   \n",
       "33  0.436209  0.549935  0.714641  0.436209  0.549935  0.714641  0.436209   \n",
       "34  0.173072  0.464444  0.688889  0.177778  0.469150  0.693595  0.187059   \n",
       "35  0.571333  0.673294  0.779176  0.569529  0.671490  0.777373  0.568627   \n",
       "36  0.525490  0.600000  0.764706  0.525490  0.600000  0.764706  0.525490   \n",
       "37  0.117346  0.415386  0.642837  0.108484  0.406523  0.633974  0.092745   \n",
       "38  0.096732  0.433203  0.617346  0.087320  0.433203  0.617895  0.071765   \n",
       "39  0.580484  0.702052  0.823438  0.573974  0.695542  0.815830  0.565294   \n",
       "40  0.189673  0.448497  0.636732  0.187320  0.446144  0.634379  0.184641   \n",
       "41  0.639281  0.606078  0.563856  0.613791  0.580588  0.538366  0.608431   \n",
       "42  0.255072  0.306497  0.551856  0.270993  0.323516  0.564170  0.299477   \n",
       "43  0.435386  0.517739  0.843229  0.435935  0.518288  0.843778  0.438170   \n",
       "44  0.823529  0.823529  0.854902  0.823529  0.823529  0.854902  0.823529   \n",
       "45  0.385712  0.471987  0.769935  0.388614  0.474889  0.772288  0.393987   \n",
       "46  0.472941  0.527843  0.774902  0.470588  0.525490  0.772549  0.467908   \n",
       "47  0.332549  0.477647  0.752157  0.334902  0.480000  0.754510  0.341503   \n",
       "48  0.034771  0.266144  0.626928  0.044183  0.275556  0.636340  0.062614   \n",
       "49  0.000915  0.363137  0.599647  0.000915  0.360784  0.599098  0.000915   \n",
       "50  0.015503  0.195895  0.290013  0.030876  0.211268  0.305386  0.019281   \n",
       "51  0.338641  0.515111  0.679817  0.328131  0.504601  0.669307  0.297320   \n",
       "52  0.192157  0.196078  0.274510  0.199216  0.203137  0.281569  0.214052   \n",
       "53  0.233856  0.324052  0.484837  0.243268  0.333464  0.494248  0.259739   \n",
       "54  0.333948  0.631987  0.765320  0.332144  0.630183  0.763516  0.330784   \n",
       "55  0.117137  0.314784  0.559752  0.130549  0.330549  0.568458  0.146928   \n",
       "56  0.382706  0.512719  0.673203  0.385608  0.519229  0.677908  0.388562   \n",
       "57  0.016601  0.263660  0.475425  0.016601  0.263660  0.475425  0.017059   \n",
       "58  0.765490  0.804706  0.840000  0.770196  0.809412  0.844706  0.776471   \n",
       "59  0.197255  0.456993  0.660915  0.197255  0.456993  0.660915  0.202680   \n",
       "\n",
       "           7         8         9  ...     67491     67492     67493     67494  \\\n",
       "0   0.227190  0.121307  0.351686  ...  0.198170  0.186405  0.221699  0.144954   \n",
       "1   0.392614  0.196536  0.646797  ...  0.394967  0.386536  0.343399  0.373974   \n",
       "2   0.105882  0.098039  0.019608  ...  0.467908  0.427778  0.254314  0.412183   \n",
       "3   0.122353  0.063529  0.227451  ...  0.078301  0.022484  0.020980  0.072810   \n",
       "4   0.881307  0.646013  0.875425  ...  0.330327  0.259739  0.251895  0.330327   \n",
       "5   0.362680  0.133072  0.426314  ...  0.077386  0.061699  0.049935  0.074248   \n",
       "6   0.271307  0.066471  0.230719  ...  0.187908  0.297712  0.140850  0.189686   \n",
       "7   0.169542  0.306797  0.249150  ...  0.477843  0.429216  0.218105  0.476340   \n",
       "8   0.400915  0.386144  0.421503  ...  0.099608  0.080000  0.056471  0.123739   \n",
       "9   0.357320  0.310261  0.471281  ...  0.161699  0.173464  0.200915  0.161699   \n",
       "10  0.308366  0.298562  0.403046  ...  0.358105  0.387974  0.170784  0.415346   \n",
       "11  0.262549  0.178235  0.150183  ...  0.418235  0.386405  0.105294  0.394092   \n",
       "12  0.135490  0.039869  0.098745  ...  0.292484  0.249346  0.163072  0.288745   \n",
       "13  0.107843  0.249020  0.158039  ...  0.014379  0.014379  0.018301  0.011516   \n",
       "14  0.798497  0.163203  0.891111  ...  0.089150  0.016144  0.000000  0.093464   \n",
       "15  0.073922  0.059412  0.207216  ...  0.884837  0.551961  0.119477  0.864039   \n",
       "16  0.623922  0.299804  0.810745  ...  0.791111  0.664706  0.341046  0.789150   \n",
       "17  0.413725  0.140588  0.651255  ...  0.035752  0.012222  0.027908  0.035294   \n",
       "18  0.069150  0.031895  0.039739  ...  0.187124  0.268562  0.045490  0.183111   \n",
       "19  0.106209  0.054444  0.214510  ...  0.007843  0.007843  0.047059  0.007843   \n",
       "20  0.576601  0.583529  0.552941  ...  0.273529  0.260392  0.202941  0.287948   \n",
       "21  0.512614  0.427712  0.532693  ...  0.076340  0.011765  0.011765  0.076340   \n",
       "22  0.636078  0.577255  0.644497  ...  0.469869  0.430654  0.324771  0.476314   \n",
       "23  0.007843  0.007843  0.007843  ...  0.007843  0.007843  0.007843  0.007843   \n",
       "24  0.303529  0.100719  0.383647  ...  0.093464  0.043725  0.003660  0.094627   \n",
       "25  0.314641  0.322484  0.314641  ...  0.011765  0.011765  0.003922  0.011765   \n",
       "26  0.007386  0.007386  0.009582  ...  0.518105  0.384771  0.235752  0.513464   \n",
       "27  0.458301  0.121046  0.669281  ...  0.077320  0.006078  0.001503  0.081294   \n",
       "28  0.243203  0.188301  0.213961  ...  0.324837  0.263399  0.161438  0.293882   \n",
       "29  0.666601  0.479542  0.763163  ...  0.671438  0.538105  0.389085  0.687503   \n",
       "30  0.694575  0.824902  0.684444  ...  0.401438  0.403399  0.530850  0.364144   \n",
       "31  0.505752  0.723399  0.301046  ...  0.445098  0.521438  0.582092  0.567595   \n",
       "32  0.182941  0.448105  0.036471  ...  0.080980  0.100588  0.089412  0.079373   \n",
       "33  0.549935  0.714641  0.436209  ...  0.036471  0.195294  0.361961  0.003569   \n",
       "34  0.473922  0.699869  0.194889  ...  0.188039  0.279608  0.479150  0.109268   \n",
       "35  0.670588  0.776471  0.569529  ...  0.071373  0.079216  0.165490  0.058484   \n",
       "36  0.600000  0.764706  0.526667  ...  0.279346  0.330327  0.463660  0.273778   \n",
       "37  0.396667  0.622157  0.080261  ...  0.063922  0.133595  0.269346  0.054065   \n",
       "38  0.433660  0.629477  0.055582  ...  0.024183  0.114837  0.200065  0.034562   \n",
       "39  0.686863  0.807516  0.558967  ...  0.152810  0.172876  0.324902  0.174641   \n",
       "40  0.443464  0.631699  0.182863  ...  0.142614  0.257516  0.365229  0.147020   \n",
       "41  0.572222  0.531503  0.632641  ...  0.142418  0.193399  0.224771  0.117739   \n",
       "42  0.351634  0.589477  0.327608  ...  0.043595  0.092614  0.336797  0.031869   \n",
       "43  0.520523  0.846013  0.441307  ...  0.165817  0.208954  0.491307  0.157516   \n",
       "44  0.823529  0.854902  0.823529  ...  0.142941  0.193922  0.260588  0.140248   \n",
       "45  0.480261  0.775882  0.399085  ...  0.481569  0.314575  0.293791  0.476797   \n",
       "46  0.522810  0.769869  0.466131  ...  0.589150  0.598954  0.653856  0.559307   \n",
       "47  0.480719  0.757190  0.348105  ...  0.310327  0.376993  0.557386  0.341203   \n",
       "48  0.288105  0.650850  0.082222  ...  0.034118  0.057647  0.229281  0.043660   \n",
       "49  0.356732  0.596405  0.001464  ...  0.018562  0.237712  0.467255  0.020248   \n",
       "50  0.188824  0.280980  0.016510  ...  0.473268  0.651699  0.737974  0.559895   \n",
       "51  0.469869  0.634575  0.287569  ...  0.443203  0.603987  0.674575  0.483634   \n",
       "52  0.217974  0.296405  0.229791  ...  0.010261  0.088235  0.098039  0.003386   \n",
       "53  0.349935  0.510719  0.278288  ...  0.122288  0.126209  0.134052  0.120967   \n",
       "54  0.628824  0.762157  0.329425  ...  0.137712  0.328039  0.495752  0.156013   \n",
       "55  0.345098  0.580523  0.155621  ...  0.214641  0.286275  0.388824  0.186745   \n",
       "56  0.524902  0.678301  0.383281  ...  0.214837  0.277451  0.385752  0.279882   \n",
       "57  0.264118  0.475882  0.018418  ...  0.076732  0.085948  0.179608  0.072654   \n",
       "58  0.815686  0.850980  0.780118  ...  0.301830  0.305752  0.388105  0.286301   \n",
       "59  0.457451  0.662876  0.209281  ...  0.238301  0.383399  0.555948  0.244026   \n",
       "\n",
       "       67495     67496     67497     67498     67499  Target  \n",
       "0   0.133190  0.168484  0.189895  0.178131  0.213425       0  \n",
       "1   0.368209  0.330824  0.389895  0.390641  0.350902       0  \n",
       "2   0.366039  0.198588  0.459556  0.413412  0.245961       0  \n",
       "3   0.020261  0.020261  0.065752  0.017908  0.017908       0  \n",
       "4   0.259739  0.251895  0.330327  0.259739  0.251895       0  \n",
       "5   0.058562  0.046797  0.071895  0.056209  0.044444       0  \n",
       "6   0.299490  0.142627  0.190235  0.300039  0.143176       0  \n",
       "7   0.426444  0.221699  0.452810  0.402209  0.200523       0  \n",
       "8   0.104131  0.080601  0.128601  0.108993  0.085464       0  \n",
       "9   0.173464  0.200915  0.161699  0.173464  0.200915       0  \n",
       "10  0.444614  0.249529  0.292052  0.323124  0.143882       0  \n",
       "11  0.362719  0.079281  0.367895  0.336523  0.051438       0  \n",
       "12  0.245608  0.159333  0.288196  0.245059  0.158784       0  \n",
       "13  0.011516  0.019359  0.009712  0.009712  0.017556       0  \n",
       "14  0.022235  0.000000  0.098170  0.027490  0.000000       0  \n",
       "15  0.531621  0.116301  0.851725  0.519307  0.109948       0  \n",
       "16  0.662745  0.339085  0.789150  0.662745  0.339085       0  \n",
       "17  0.011765  0.027451  0.035294  0.011765  0.027451       0  \n",
       "18  0.264183  0.041294  0.182013  0.264183  0.040745       0  \n",
       "19  0.007843  0.047059  0.007843  0.007843  0.047059       0  \n",
       "20  0.274261  0.217359  0.296261  0.284222  0.225673       0  \n",
       "21  0.011765  0.011765  0.076340  0.011765  0.011765       0  \n",
       "22  0.437098  0.331216  0.482275  0.443059  0.337176       0  \n",
       "23  0.007843  0.007843  0.007843  0.007843  0.007843       0  \n",
       "24  0.045190  0.005948  0.066627  0.020797  0.003203       0  \n",
       "25  0.011765  0.003922  0.011765  0.011765  0.003922       0  \n",
       "26  0.380131  0.231111  0.511111  0.377778  0.228758       0  \n",
       "27  0.010471  0.003804  0.081791  0.011020  0.004092       0  \n",
       "28  0.236627  0.134667  0.290013  0.233281  0.131320       0  \n",
       "29  0.554170  0.405150  0.700680  0.567346  0.418327       0  \n",
       "30  0.364144  0.497477  0.308379  0.308379  0.441712       1  \n",
       "31  0.643935  0.704588  0.335203  0.411542  0.472196       1  \n",
       "32  0.095974  0.089307  0.071059  0.087660  0.080993       1  \n",
       "33  0.155608  0.324235  0.002863  0.153098  0.321725       1  \n",
       "34  0.203190  0.408824  0.049111  0.144993  0.355882       1  \n",
       "35  0.066327  0.156523  0.060680  0.068523  0.158719       1  \n",
       "36  0.324758  0.458092  0.272052  0.323033  0.456366       1  \n",
       "37  0.116810  0.250144  0.064418  0.127163  0.260497       1  \n",
       "38  0.117830  0.201464  0.043817  0.127085  0.209621       1  \n",
       "39  0.194248  0.353464  0.200523  0.220131  0.384052       1  \n",
       "40  0.262745  0.373190  0.147725  0.265098  0.374993       1  \n",
       "41  0.168719  0.200092  0.124719  0.175699  0.207072       1  \n",
       "42  0.074458  0.317595  0.017438  0.058928  0.302065       1  \n",
       "43  0.196732  0.479085  0.171634  0.210850  0.493203       1  \n",
       "44  0.191229  0.257895  0.139699  0.190680  0.257346       1  \n",
       "45  0.313268  0.292484  0.478758  0.315229  0.294444       1  \n",
       "46  0.571072  0.632248  0.449425  0.461190  0.527072       1  \n",
       "47  0.407869  0.588261  0.360340  0.427007  0.607399       1  \n",
       "48  0.061163  0.232183  0.025621  0.044928  0.210536       1  \n",
       "49  0.239216  0.468758  0.019699  0.239216  0.468758       1  \n",
       "50  0.736366  0.818719  0.502170  0.678641  0.760993       1  \n",
       "51  0.644418  0.715007  0.532732  0.693516  0.764105       1  \n",
       "52  0.085098  0.089020  0.000484  0.082745  0.086667       1  \n",
       "53  0.124889  0.132732  0.047085  0.051007  0.058850       1  \n",
       "54  0.346340  0.514052  0.165817  0.356144  0.523856       1  \n",
       "55  0.263895  0.361020  0.191608  0.269856  0.366980       1  \n",
       "56  0.350732  0.463895  0.267882  0.343438  0.459660       1  \n",
       "57  0.085948  0.174327  0.076261  0.094967  0.181542       1  \n",
       "58  0.290222  0.372575  0.257595  0.261516  0.343869       1  \n",
       "59  0.389673  0.561948  0.247634  0.394379  0.566105       1  \n",
       "\n",
       "[60 rows x 67501 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Les categories des images \n",
    "Categories=['car','ship']\n",
    "\n",
    "\n",
    "\n",
    "flat_data_arr=[]\n",
    "target_arr=[]\n",
    "\n",
    "#Chemin de la BD\n",
    "datadir='./DB'\n",
    "\n",
    "#Parcourir les categories\n",
    "for i in Categories:\n",
    "  print(f'loading... category : {i}')\n",
    "  path=os.path.join(datadir,i)\n",
    "  #PreTraitement sur chaque image et les stocker dans le tableau \"flat_data_arr\"\n",
    "  for img in os.listdir(path):\n",
    "    img_array=imread(os.path.join(path,img))\n",
    "    img_resized=resize(img_array,(150,150,3))\n",
    "    flat_data_arr.append(img_resized.flatten())\n",
    "    target_arr.append(Categories.index(i))\n",
    "  print(f'loaded category:{i} successfully')\n",
    "\n",
    "#Affectation \"image : etiquette categorie\" dans le dataframe \"df\"\n",
    "flat_data=np.array(flat_data_arr)\n",
    "target=np.array(target_arr)\n",
    "df=pd.DataFrame(flat_data)\n",
    "df['Target']=target\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "52609ee6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Splitted Successfully\n"
     ]
    }
   ],
   "source": [
    "#inputs\n",
    "x=df.iloc[:,:-1]\n",
    "#outputs\n",
    "y=df.iloc[:,-1]\n",
    "\n",
    "#division des donnees en 2 parties : donnees d'apprentissage et de test\n",
    "x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.30,random_state=77,stratify=y)\n",
    "print('Splitted Successfully')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "30556ee6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The training of the model is started, please wait for while as it may take few minutes to complete\n",
      "....\n",
      "The Model is trained well with the given images\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'C': 10, 'gamma': 0.0001, 'kernel': 'rbf'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Apprentissage et construction de model\n",
    "\n",
    "param_grid={'C':[0.1,1,10,100],'gamma':[0.0001,0.001,0.1,1],'kernel':['rbf','poly']}\n",
    "#svc : support vector classifier\n",
    "svc=svm.SVC(probability=True)\n",
    "print(\"The training of the model is started, please wait for while as it may take few minutes to complete\")\n",
    "#Parcourir les hyperparametres de \"SVC\" et selectionner les meilleurs parametres pour notre model avec \"GridSearchCV\"\n",
    "model=GridSearchCV(svc,param_grid)\n",
    "print(\"....\")\n",
    "model.fit(x_train,y_train)\n",
    "print(\"The Model is trained well with the given images\")\n",
    "#Les meilleurs parametres\n",
    "model.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3736ec99",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The predicted Data is :\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Prediction de nos donnees test\n",
    "y_pred=model.predict(x_test)\n",
    "print(\"The predicted Data is :\")\n",
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9bd667fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The actual data is:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The actual data is:\")\n",
    "np.array(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ccb4237b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The model is 100.0% accurate\n"
     ]
    }
   ],
   "source": [
    "#pourcentage de precision\n",
    "print(f\"The model is {accuracy_score(y_pred,y_test)*100}% accurate\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "63718aa9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pickle is dumped successfully\n"
     ]
    }
   ],
   "source": [
    "#Enregistrer le model dans le disque\n",
    "pickle.dump(model,open('img_model.p','wb'))\n",
    "print(\"Pickle is dumped successfully\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ff7f87e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter URL of Image./DB/car/29032.jpg\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "car = 97.18362426082743%\n",
      "ship = 2.816375739172571%\n",
      "The predicted image is : car\n"
     ]
    }
   ],
   "source": [
    "#Test du model\n",
    "\n",
    "model=pickle.load(open('img_model.p','rb'))\n",
    "\n",
    "url=input('Enter URL of Image')\n",
    "img=imread(url)\n",
    "plt.imshow(img)\n",
    "plt.show()\n",
    "img_resize=resize(img,(150,150,3))\n",
    "l=[img_resize.flatten()]\n",
    "probability=model.predict_proba(l)\n",
    "for ind,val in enumerate(Categories):\n",
    "  print(f'{val} = {probability[0][ind]*100}%')\n",
    "print(\"The predicted image is : \"+Categories[model.predict(l)[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8ed5f32",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}