NN and CNN.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "train = pd.read_csv('traindata.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>252</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>250</td>\n",
       "      <td>252</td>\n",
       "      <td>254</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>250</td>\n",
       "      <td>251</td>\n",
       "      <td>254</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
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       "      <th>20</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
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       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>250</td>\n",
       "      <td>252</td>\n",
       "      <td>254</td>\n",
       "      <td>254</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
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       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>249</td>\n",
       "      <td>251</td>\n",
       "      <td>252</td>\n",
       "      <td>254</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>248</td>\n",
       "      <td>251</td>\n",
       "      <td>252</td>\n",
       "      <td>254</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>249</td>\n",
       "      <td>250</td>\n",
       "      <td>252</td>\n",
       "      <td>254</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>253</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>249</td>\n",
       "      <td>250</td>\n",
       "      <td>253</td>\n",
       "      <td>254</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1400</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1401</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1402</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1403</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1404</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1405</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1406</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1407</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1408</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1409</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1410</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1411</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1412</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>246</td>\n",
       "      <td>251</td>\n",
       "      <td>253</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1413</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1414</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>251</td>\n",
       "      <td>253</td>\n",
       "      <td>254</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1415</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1416</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <th>1417</th>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
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       "      <th>1426</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <th>1427</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1428</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1429</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1430 rows × 14401 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        0    1    2    3    4    5    6    7    8    9  ...    14391  14392  \\\n",
       "0     255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1     255  255  255  255  255  255  255  255  255  255  ...      250    253   \n",
       "2     255  255  255  255  255  255  255  255  255  255  ...      249    250   \n",
       "3     255  255  255  255  255  255  255  255  255  255  ...      249    251   \n",
       "4     255  255  255  255  255  255  255  255  255  255  ...      251    252   \n",
       "5     255  255  255  255  255  255  255  255  255  255  ...      254    255   \n",
       "6     255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "7     255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "8     255  255  255  255  255  255  255  255  255  255  ...      250    251   \n",
       "9     255  255  255  255  255  255  255  255  255  255  ...      250    251   \n",
       "10    255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "11    255  255  255  255  255  255  255  255  255  255  ...      249    250   \n",
       "12    255  255  255  255  255  255  255  255  255  255  ...      253    255   \n",
       "13    255  255  255  255  255  255  255  255  255  255  ...      250    251   \n",
       "14    255  255  255  255  255  255  255  255  255  255  ...      250    250   \n",
       "15    255  255  255  255  255  255  255  255  255  255  ...      253    255   \n",
       "16    255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "17    255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "18    255  255  255  255  255  255  255  255  255  255  ...      250    250   \n",
       "19    255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "20    255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "21    255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "22    255  255  255  255  255  255  255  255  255  255  ...      250    252   \n",
       "23    255  255  255  255  255  255  255  255  255  255  ...      249    251   \n",
       "24    255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "25    255  255  255  255  255  255  255  255  255  255  ...      248    251   \n",
       "26    255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "27    255  255  255  255  255  255  255  255  255  255  ...      249    250   \n",
       "28    255  255  255  255  255  255  255  255  255  255  ...      253    255   \n",
       "29    255  255  255  255  255  255  255  255  255  255  ...      249    250   \n",
       "...   ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...      ...    ...   \n",
       "1400  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1401  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1402  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1403  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1404  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1405  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
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       "1407  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1408  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
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       "1410  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1411  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
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       "1415  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
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       "1418  255  255  255  255  255  255  255  255  255  253  ...      255    255   \n",
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       "1424  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1425  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
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       "1428  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "1429  255  255  255  255  255  255  255  255  255  255  ...      255    255   \n",
       "\n",
       "      14393  14394  14395  14396  14397  14398  14399  label  \n",
       "0       255    255    255    255    255    255    255      A  \n",
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       "10      255    255    255    255    255    255    255      A  \n",
       "11      251    253    255    255    255    255    255      A  \n",
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       "14      252    254    255    255    255    255    255      A  \n",
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       "16      255    255    255    255    255    255    255      A  \n",
       "17      255    255    255    255    255    255    255      A  \n",
       "18      251    254    255    255    255    255    255      A  \n",
       "19      255    255    255    255    255    255    255      A  \n",
       "20      255    255    255    255    255    255    255      A  \n",
       "21      255    255    255    255    255    255    255      A  \n",
       "22      254    254    255    255    255    255    255      A  \n",
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       "24      255    255    255    255    255    255    255      A  \n",
       "25      252    254    255    255    255    255    255      A  \n",
       "26      255    255    255    255    255    255    255      A  \n",
       "27      252    254    255    255    255    255    255      A  \n",
       "28      255    255    255    255    255    255    255      A  \n",
       "29      253    254    255    255    255    255    255      A  \n",
       "...     ...    ...    ...    ...    ...    ...    ...    ...  \n",
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       "1428    255    255    255    255    255    255    255      Z  \n",
       "1429    255    255    255    255    255    255    255      Z  \n",
       "\n",
       "[1430 rows x 14401 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train_shuffle = train.sample(frac=1).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "NNtrain = train_shuffle.drop('label', axis=1)\n",
    "NNtrain_label = train_shuffle['label']\n",
    "# normalize\n",
    "train1 = NNtrain/225\n",
    "train1['label'] = NNtrain_label"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PCA and Neural Network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Vi672/Yzkd7BUm/dP0tHAecD7SVZeuEHqbCZJr9LWvQS4LiKOT1/zASS9H9/L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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f287958ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import decomposition\n",
    "from sklearn import datasets\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "## PCA decomposition\n",
    "pca = decomposition.PCA(n_components=200) #Finds first 200 PCs\n",
    "pca.fit(train1.drop('label', axis=1))\n",
    "plt.plot(pca.explained_variance_ratio_)\n",
    "plt.ylabel('% of variance explained')\n",
    "#plot reaches asymptote at around 50, which is optimal number of PCs to use. \n",
    "\n",
    "## PCA decomposition with optimal number of PCs\n",
    "#decompose train data\n",
    "pca = decomposition.PCA(n_components=50) #use first 3 PCs (update to 100 later)\n",
    "pca.fit(train1.drop('label', axis=1))\n",
    "PCtrain = pd.DataFrame(pca.transform(train1.drop('label', axis=1)))\n",
    "PCtrain['label'] = train1['label']\n",
    "\n",
    "#decompose test data\n",
    "#pca.fit(test)\n",
    "#PCtest = pd.DataFrame(pca.transform(test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MLPClassifier(activation='tanh', alpha=1e-05, batch_size='auto', beta_1=0.9,\n",
       "       beta_2=0.999, early_stopping=False, epsilon=1e-08,\n",
       "       hidden_layer_sizes=(2500,), learning_rate='constant',\n",
       "       learning_rate_init=0.001, max_iter=600, momentum=0.9,\n",
       "       nesterovs_momentum=True, power_t=0.5, random_state=0, shuffle=False,\n",
       "       solver='lbgfs', tol=0.0001, validation_fraction=0.1, verbose=False,\n",
       "       warm_start=False)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neural_network import MLPClassifier\n",
    "y = PCtrain['label'][0:1001]\n",
    "X = PCtrain.drop('label', axis=1)[0:1001]\n",
    "clf = MLPClassifier(solver='lbgfs', alpha=1e-5,\n",
    "                    hidden_layer_sizes=(2500,), random_state=0, activation='tanh',\n",
    "                   max_iter=600)\n",
    "clf.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification report for classifier MLPClassifier(activation='tanh', alpha=1e-05, batch_size='auto', beta_1=0.9,\n",
      "       beta_2=0.999, early_stopping=False, epsilon=1e-08,\n",
      "       hidden_layer_sizes=(2500,), learning_rate='constant',\n",
      "       learning_rate_init=0.001, max_iter=600, momentum=0.9,\n",
      "       nesterovs_momentum=True, power_t=0.5, random_state=0, shuffle=False,\n",
      "       solver='lbgfs', tol=0.0001, validation_fraction=0.1, verbose=False,\n",
      "       warm_start=False):\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          A       0.88      0.88      0.88        16\n",
      "          B       1.00      0.91      0.95        22\n",
      "          C       1.00      0.88      0.94        17\n",
      "          D       0.93      1.00      0.97        14\n",
      "          E       0.95      0.82      0.88        22\n",
      "          F       0.86      1.00      0.92        18\n",
      "          G       1.00      1.00      1.00        14\n",
      "          H       0.95      0.90      0.92        20\n",
      "          I       0.89      0.89      0.89        18\n",
      "          J       0.92      0.86      0.89        14\n",
      "          K       0.92      0.86      0.89        14\n",
      "          L       0.83      1.00      0.91        15\n",
      "          M       0.81      0.81      0.81        16\n",
      "          N       0.95      0.95      0.95        22\n",
      "          O       0.93      1.00      0.97        14\n",
      "          P       1.00      1.00      1.00        18\n",
      "          Q       0.80      0.92      0.86        13\n",
      "          R       1.00      0.83      0.91        24\n",
      "          S       0.73      0.85      0.79        13\n",
      "          T       1.00      0.94      0.97        16\n",
      "          U       1.00      1.00      1.00        17\n",
      "          V       0.90      0.90      0.90        10\n",
      "          W       0.93      1.00      0.97        14\n",
      "          X       0.93      1.00      0.97        14\n",
      "          Y       0.90      1.00      0.95        19\n",
      "          Z       1.00      0.93      0.97        15\n",
      "\n",
      "avg / total       0.93      0.93      0.93       429\n",
      "\n",
      "\n",
      "Confusion matrix:\n",
      "[[14  0  0  0  0  0  0  1  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0 20  0  1  0  0  0  0  0  0  0  0  0  0  1  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0 15  0  1  0  0  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0 14  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0 18  2  0  0  1  0  1  0  0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0 18  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0 14  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 1  0  0  0  0  0  0 18  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0 16  0  0  0  0  0  0  0  0  0  2  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0 12  0  0  0  0  0  0  0  0  2  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0 12  1  1  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0 15  0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0 13  1  0  0  0  0  0  0  0  1  0  0\n",
      "   1  0]\n",
      " [ 1  0  0  0  0  0  0  0  0  0  0  0  0 21  0  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0  0  0 14  0  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 18  0  0  0  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 12  0  0  0  0  0  1  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  1  0  0  0  0  2 20  0  0  0  0  0  1\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  1  0  0  0  0  0  0  1  0 11  0  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0  0  0  0 15  0  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 17  0  0  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  9  0  0\n",
      "   1  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 14  0\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 14\n",
      "   0  0]\n",
      " [ 0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0\n",
      "  19  0]\n",
      " [ 0  0  0  0  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   0 14]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn import  metrics\n",
    "#accuracy and confusion matrix\n",
    "predicted = clf.predict(PCtrain.drop('label', axis=1)[1001:1430])\n",
    "expected = PCtrain['label'][1001:1430]\n",
    "\n",
    "print(\"Classification report for classifier %s:\\n%s\\n\"\n",
    "      % (clf, metrics.classification_report(expected, predicted)))\n",
    "print(\"Confusion matrix:\\n%s\" % metrics.confusion_matrix(expected, predicted))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1f2c0cd7ef0>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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sAENDQ+HldfeUj06nQ2JiIgAgMTER+/fvt012RESkOoJg3cNeZK0C7ezshK+vLwDAz8/P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\niMgpsQMkIiKn9P8DKzygT7DVNxoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2c0c4b828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.heatmap(metrics.confusion_matrix(expected, predicted), fmt='d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.92540792540792538"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "accuracy_score(expected, predicted)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Tensorflow Neural Network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pickle\n",
    "import tensorflow as tf\n",
    "from os.path import isfile, isdir\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def one_hot_encoding(data, numberOfClass):\n",
    "    from sklearn import preprocessing\n",
    "    lb = preprocessing.LabelBinarizer()\n",
    "    lb.fit(range(numberOfClass))\n",
    "    return lb.transform(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "TrainData = NNtrain/255\n",
    "TrainLabel = train_shuffle.values[:, -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import string\n",
    "alph = string.ascii_uppercase\n",
    "for i in range(1430):\n",
    "    for j in range(26):\n",
    "        if TrainLabel[i] == alph[j]:\n",
    "            TrainLabel[i]=j\n",
    "TrainLabel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = TrainLabel.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "one_hot_trainLabel = one_hot_encoding(x, 26)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one_hot_trainLabel[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def getInputTensor(features, numberOfClass):\n",
    "    inputT = tf.placeholder(dtype = tf.float32, shape = (None, features), name = 'input')\n",
    "    labelT = tf.placeholder(dtype = tf.float32, shape = (None, numberOfClass), name = 'label')\n",
    "    keep_prob = tf.placeholder(dtype = tf.float32)\n",
    "    \n",
    "    return inputT, labelT, keep_prob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def hiddenLayer(inputT, numberOfNodes):\n",
    "    inputSize = inputT.get_shape().as_list()[1]\n",
    "    # create weights & biases\n",
    "    weights = tf.Variable(tf.truncated_normal((inputSize, numberOfNodes)), dtype = tf.float32)\n",
    "    biases = tf.zeros((numberOfNodes), dtype = tf.float32)\n",
    "    # output of hidden nodes\n",
    "    hiddenNodes = tf.add(tf.matmul(inputT, weights), biases)\n",
    "    hiddenOutput = tf.nn.sigmoid(hiddenNodes)\n",
    "    \n",
    "    return hiddenOutput"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def outputLayer(hiddenOutput, numberOfClass):\n",
    "    inputSize = hiddenOutput.get_shape().as_list()[1]\n",
    "    # create weights & biases\n",
    "    weights = tf.Variable(tf.truncated_normal((inputSize, numberOfClass)), dtype = tf.float32)\n",
    "    biases = tf.zeros((numberOfClass), dtype = tf.float32)\n",
    "    # output\n",
    "    output = tf.add(tf.matmul(hiddenOutput, weights), biases)\n",
    "    \n",
    "    return output\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def build_nn(inputT, numberOfNodes, numberOfClass, keep_prob):\n",
    "    # fully_connected layers\n",
    "    fc1 = hiddenLayer(inputT, numberOfNodes)\n",
    "    output = outputLayer(fc1, numberOfClass)\n",
    "    \n",
    "    return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "numberOfNodes = 2500\n",
    "batchSize = 128\n",
    "numberOfEpoch = 40\n",
    "learningRate = 0.0001\n",
    "keep_prob_rate = 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Build Neural Network graph\n",
    "numberOfClass = 26\n",
    "imageSize = (120, 120)\n",
    "features = np.prod(imageSize)\n",
    "graph = tf.Graph()\n",
    "tf.reset_default_graph()\n",
    "with graph.as_default():\n",
    "    \n",
    "    # get inputs\n",
    "    inputT, labelT, keep_prob = getInputTensor(features, numberOfClass)\n",
    "    \n",
    "    # build fully-conneted neural network\n",
    "    logits = build_nn(inputT, numberOfNodes, numberOfClass, keep_prob)\n",
    "    \n",
    "    # softmax with cross entropy\n",
    "    probability = tf.nn.softmax(logits, name = 'probability')\n",
    "    \n",
    "    # Cost\n",
    "    cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits = logits, labels = labelT))\n",
    "    \n",
    "    # optimizer\n",
    "    optimizer = tf.train.AdamOptimizer(learning_rate = learningRate).minimize(cost)\n",
    "    \n",
    "    # accuracy\n",
    "    correctPrediction = tf.equal(tf.argmax(probability, 1),tf.argmax(labelT, 1))\n",
    "    accuracy = tf.reduce_mean(tf.cast(correctPrediction, tf.float32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def printResult(epoch, numberOfEpoch, trainLoss, validationLoss, validationAccuracy):\n",
    "    print(\"Epoch: {}/{}\".format(epoch+1, numberOfEpoch),\n",
    "         '\\tTraining Loss: {:.3f}'.format(trainLoss),\n",
    "         '\\tValidation Loss: {:.3f}'.format(validationLoss),\n",
    "         '\\tAccuracy: {:.2f}%'.format(validationAccuracy*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1/40 \tTraining Loss: 44.552 \tValidation Loss: 45.760 \tAccuracy: 5.13%\n",
      "Epoch: 2/40 \tTraining Loss: 36.225 \tValidation Loss: 32.736 \tAccuracy: 9.79%\n",
      "Epoch: 3/40 \tTraining Loss: 28.233 \tValidation Loss: 26.668 \tAccuracy: 10.02%\n",
      "Epoch: 4/40 \tTraining Loss: 21.481 \tValidation Loss: 21.867 \tAccuracy: 17.25%\n",
      "Epoch: 5/40 \tTraining Loss: 14.924 \tValidation Loss: 16.470 \tAccuracy: 21.21%\n",
      "Epoch: 6/40 \tTraining Loss: 16.964 \tValidation Loss: 13.141 \tAccuracy: 29.60%\n",
      "Epoch: 7/40 \tTraining Loss: 12.632 \tValidation Loss: 12.247 \tAccuracy: 31.24%\n",
      "Epoch: 8/40 \tTraining Loss: 7.492 \tValidation Loss: 9.449 \tAccuracy: 38.46%\n",
      "Epoch: 9/40 \tTraining Loss: 6.797 \tValidation Loss: 7.488 \tAccuracy: 46.62%\n",
      "Epoch: 10/40 \tTraining Loss: 6.270 \tValidation Loss: 6.032 \tAccuracy: 52.45%\n",
      "Epoch: 11/40 \tTraining Loss: 2.866 \tValidation Loss: 5.457 \tAccuracy: 57.34%\n",
      "Epoch: 12/40 \tTraining Loss: 2.725 \tValidation Loss: 4.322 \tAccuracy: 65.50%\n",
      "Epoch: 13/40 \tTraining Loss: 3.521 \tValidation Loss: 3.126 \tAccuracy: 71.79%\n",
      "Epoch: 14/40 \tTraining Loss: 2.073 \tValidation Loss: 2.606 \tAccuracy: 72.96%\n",
      "Epoch: 15/40 \tTraining Loss: 2.064 \tValidation Loss: 2.019 \tAccuracy: 76.92%\n",
      "Epoch: 16/40 \tTraining Loss: 2.985 \tValidation Loss: 2.285 \tAccuracy: 76.46%\n",
      "Epoch: 17/40 \tTraining Loss: 2.254 \tValidation Loss: 1.635 \tAccuracy: 80.19%\n",
      "Epoch: 18/40 \tTraining Loss: 1.225 \tValidation Loss: 1.351 \tAccuracy: 85.55%\n",
      "Epoch: 19/40 \tTraining Loss: 1.314 \tValidation Loss: 1.070 \tAccuracy: 86.01%\n",
      "Epoch: 20/40 \tTraining Loss: 0.514 \tValidation Loss: 0.944 \tAccuracy: 87.88%\n",
      "Epoch: 21/40 \tTraining Loss: 0.449 \tValidation Loss: 0.965 \tAccuracy: 86.25%\n",
      "Epoch: 22/40 \tTraining Loss: 0.793 \tValidation Loss: 0.792 \tAccuracy: 88.34%\n",
      "Epoch: 23/40 \tTraining Loss: 0.118 \tValidation Loss: 0.792 \tAccuracy: 90.21%\n",
      "Epoch: 24/40 \tTraining Loss: 0.786 \tValidation Loss: 0.460 \tAccuracy: 93.47%\n",
      "Epoch: 25/40 \tTraining Loss: 0.246 \tValidation Loss: 0.436 \tAccuracy: 95.34%\n",
      "Epoch: 26/40 \tTraining Loss: 0.358 \tValidation Loss: 0.456 \tAccuracy: 94.41%\n",
      "Epoch: 27/40 \tTraining Loss: 0.375 \tValidation Loss: 0.298 \tAccuracy: 96.74%\n",
      "Epoch: 28/40 \tTraining Loss: 0.212 \tValidation Loss: 0.255 \tAccuracy: 96.97%\n",
      "Epoch: 29/40 \tTraining Loss: 0.470 \tValidation Loss: 0.351 \tAccuracy: 97.20%\n",
      "Epoch: 30/40 \tTraining Loss: 0.166 \tValidation Loss: 0.225 \tAccuracy: 97.44%\n",
      "Epoch: 31/40 \tTraining Loss: 0.460 \tValidation Loss: 0.165 \tAccuracy: 97.90%\n",
      "Epoch: 32/40 \tTraining Loss: 0.150 \tValidation Loss: 0.219 \tAccuracy: 97.44%\n",
      "Epoch: 33/40 \tTraining Loss: 0.166 \tValidation Loss: 0.122 \tAccuracy: 98.37%\n",
      "Epoch: 34/40 \tTraining Loss: 0.043 \tValidation Loss: 0.118 \tAccuracy: 98.60%\n",
      "Epoch: 35/40 \tTraining Loss: 0.143 \tValidation Loss: 0.190 \tAccuracy: 98.60%\n",
      "Epoch: 36/40 \tTraining Loss: 0.202 \tValidation Loss: 0.053 \tAccuracy: 99.53%\n",
      "Epoch: 37/40 \tTraining Loss: 0.044 \tValidation Loss: 0.127 \tAccuracy: 98.83%\n",
      "Epoch: 38/40 \tTraining Loss: 0.034 \tValidation Loss: 0.060 \tAccuracy: 98.60%\n",
      "Epoch: 39/40 \tTraining Loss: 0.037 \tValidation Loss: 0.101 \tAccuracy: 98.60%\n",
      "Epoch: 40/40 \tTraining Loss: 0.014 \tValidation Loss: 0.078 \tAccuracy: 99.30%\n"
     ]
    }
   ],
   "source": [
    "save_dir = \"save/\"\n",
    "with tf.Session(graph=graph) as sess:\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "    \n",
    "    for epoch in range(numberOfEpoch):\n",
    "        # training data & validation data\n",
    "        train_x, val_x, train_y, val_y = train_test_split(TrainData, one_hot_trainLabel,test_size = 0.3)   \n",
    "        # training loss\n",
    "        for i in range(0, len(train_x), batchSize):\n",
    "            trainLoss, _, _ = sess.run([cost, probability, optimizer], feed_dict = {\n",
    "                inputT: train_x[i: i+batchSize],\n",
    "                labelT: train_y[i: i+batchSize],\n",
    "                keep_prob: keep_prob_rate   \n",
    "            })\n",
    "            \n",
    "        # validation loss\n",
    "        valAcc, valLoss = sess.run([accuracy, cost], feed_dict ={\n",
    "            inputT: val_x,\n",
    "            labelT: val_y,\n",
    "            keep_prob: 1.0\n",
    "        })\n",
    "        \n",
    "        \n",
    "        # print out\n",
    "        printResult(epoch, numberOfEpoch, trainLoss, valLoss, valAcc)\n",
    "    # save\n",
    "    saver = tf.train.Saver()\n",
    "    saver.save(sess, save_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test = pd.read_csv('testcolor.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test_shuffle = test.sample(frac=1).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Testdata = test_shuffle.drop('label',axis=1)/255\n",
    "TestLabel = test_shuffle['label']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# test result\n",
    "\n",
    "loaded_Graph = tf.Graph()\n",
    "with tf.Session(graph=loaded_Graph) as sess:\n",
    "    loader = tf.train.import_meta_graph(save_dir +'.meta')\n",
    "    loader.restore(sess, save_dir)    \n",
    "    # get tensors\n",
    "    loaded_x = loaded_Graph.get_tensor_by_name('input:0')\n",
    "    loaded_y = loaded_Graph.get_tensor_by_name('label:0')\n",
    "    loaded_prob = loaded_Graph.get_tensor_by_name('probability:0')\n",
    "    \n",
    "    prob = sess.run(tf.argmax(loaded_prob,1), feed_dict = {loaded_x: Testdata})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([12,  2,  6, ..., 18, 17,  3])"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prob = prob.astype(int)\n",
    "prob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['C', 'P', 'T', ..., 'M', 'L', 'U'], dtype=object)"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "true = TestLabel.values\n",
    "true"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ABCDEFGHIJKLMNOPQRSTUVWXYZ'"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for i in range(len(true)):\n",
    "    for j in range(26):\n",
    "        if true[i] == alph[j]:\n",
    "            true[i] = j\n",
    "true = true.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2, 15, 19, ..., 12, 11, 20])"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "true"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x21d1b6d3278>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DU089hYCAAAQFBeGee+6BqyuPayEiIsdhctYKCQnBK6+8gqamJnh7e2PJkiXw8fHBvffe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\nUe7SUfV1PjT1QdF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      "text/plain": [
       "<matplotlib.figure.Figure at 0x21d020972e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "import seaborn as sns\n",
    "sns.heatmap(metrics.confusion_matrix(true, prob), fmt='d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.13187285223367698"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "accuracy_score(true, prob)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Convolutional neural network with colorful dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pickle\n",
    "import tensorflow as tf\n",
    "from os.path import isfile, isdir\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>label</th>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>...</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>255</td>\n",
       "      <td>255</td>\n",
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       "      <td>255</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2298</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2299</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2300</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2301</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2302</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2303</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2304</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2305</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2306</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2307</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2308</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2309</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2310</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2311</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2312</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2313</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2314</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2315</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2316</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2317</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2318</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2319</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2320</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2321</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2322</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2323</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2324</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2325</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2326</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2327</th>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>...</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>255</td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2328 rows × 2501 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        0    1    2    3    4    5    6    7    8    9  ...    2491  2492  \\\n",
       "0     255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "1     255  255  255  255  255  255  255  255  255  255  ...       0     0   \n",
       "2     255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "3       0    0    0    0    0    0    0    0    0    0  ...       0     0   \n",
       "4       0    0    0    0    0    0    0    0    0    0  ...     255   255   \n",
       "5       0    0    0    0    0    0    0    0    0    0  ...     255   255   \n",
       "6       0    0    0    0    0    0    0    0    0    0  ...     255   255   \n",
       "7     255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "8     255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "9     255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "10    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "11    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "12    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "13    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "14    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "15    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "16    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "17    255  255  255  255  255  255  255  255  255  255  ...       0     0   \n",
       "18    255  255  255  255  255  255  255  255  255  255  ...       0     0   \n",
       "19    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "20    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "21    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "22    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "23    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "24    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "25    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "26    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "27    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "28    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "29    255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "...   ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...     ...   ...   \n",
       "2298    0    0    0    0    0    0    0    0    0    0  ...     255   255   \n",
       "2299    0    0    0    0  255    0  255    0    0    0  ...     255   255   \n",
       "2300  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2301  255  255  255  255  255  255  255  255  255  255  ...       0   255   \n",
       "2302  255  255  255  255  255  255  255    0    0    0  ...       0     0   \n",
       "2303  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2304  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2305  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2306  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2307    0    0    0    0    0    0    0    0    0    0  ...       0     0   \n",
       "2308  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2309  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2310  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2311  255  255  255  255  255  255  255  255  255  255  ...       0     0   \n",
       "2312  255  255  255  255  255  255  255    0    0    0  ...     255   255   \n",
       "2313    0    0    0    0    0    0    0    0    0    0  ...     255   255   \n",
       "2314  255  255  255  255  255  255  255  255  255  255  ...       0     0   \n",
       "2315  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2316  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2317  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2318  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2319  255  255  255  255  255    0  255  255  255  255  ...       0     0   \n",
       "2320  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2321  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2322  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2323  255  255  255  255  255  255  255  255  255  255  ...       0     0   \n",
       "2324    0    0    0  255    0    0    0    0  255  255  ...     255   255   \n",
       "2325    0    0    0    0    0    0    0    0    0    0  ...     255   255   \n",
       "2326  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "2327  255  255  255  255  255  255  255  255  255  255  ...     255   255   \n",
       "\n",
       "      2493  2494  2495  2496  2497  2498  2499  label  \n",
       "0      255   255   255   255   255   255   255      A  \n",
       "1        0     0     0     0   255   255   255      A  \n",
       "2      255   255   255   255   255   255   255      A  \n",
       "3        0     0     0     0   255   255   255      A  \n",
       "4      255   255     0     0   255   255   255      A  \n",
       "5      255   255   255   255   255   255   255      A  \n",
       "6      255   255   255   255   255   255   255      A  \n",
       "7      255   255     0   255     0   255   255      A  \n",
       "8      255   255   255   255   255   255   255      A  \n",
       "9      255   255   255   255   255   255   255      A  \n",
       "10     255   255   255   255   255   255   255      A  \n",
       "11     255   255   255   255   255   255   255      A  \n",
       "12     255   255   255   255   255   255   255      A  \n",
       "13     255   255   255   255   255   255   255      A  \n",
       "14     255   255   255   255   255     0   255      A  \n",
       "15     255   255   255   255   255   255   255      A  \n",
       "16     255   255   255   255   255   255   255      A  \n",
       "17       0   255   255   255   255   255     0      A  \n",
       "18       0     0     0     0   255   255   255      A  \n",
       "19     255   255   255   255     0     0     0      A  \n",
       "20     255   255   255   255   255   255   255      A  \n",
       "21     255   255   255   255   255   255   255      A  \n",
       "22     255   255   255   255   255   255   255      A  \n",
       "23     255   255   255   255   255   255   255      A  \n",
       "24     255   255   255   255   255   255   255      A  \n",
       "25     255   255   255   255   255   255   255      A  \n",
       "26     255   255   255   255   255   255   255      A  \n",
       "27     255   255   255   255   255   255   255      A  \n",
       "28     255   255   255   255   255   255   255      A  \n",
       "29     255   255   255   255   255   255   255      A  \n",
       "...    ...   ...   ...   ...   ...   ...   ...    ...  \n",
       "2298   255   255   255     0     0     0     0      Z  \n",
       "2299   255   255   255   255   255   255   255      Z  \n",
       "2300   255   255   255   255   255   255   255      Z  \n",
       "2301     0   255     0   255     0   255     0      Z  \n",
       "2302     0     0     0   255   255   255   255      Z  \n",
       "2303   255   255   255   255   255   255   255      Z  \n",
       "2304   255   255   255   255   255   255   255      Z  \n",
       "2305   255   255   255   255   255   255   255      Z  \n",
       "2306   255   255   255   255   255   255   255      Z  \n",
       "2307     0     0     0     0     0     0     0      Z  \n",
       "2308   255   255   255   255   255   255   255      Z  \n",
       "2309   255   255   255   255   255   255   255      Z  \n",
       "2310   255   255   255   255   255   255   255      Z  \n",
       "2311     0     0     0     0   255   255   255      Z  \n",
       "2312   255   255   255   255   255   255   255      Z  \n",
       "2313   255   255   255   255   255   255   255      Z  \n",
       "2314     0     0     0   255   255   255   255      Z  \n",
       "2315   255   255   255   255   255   255   255      Z  \n",
       "2316   255   255   255   255   255   255   255      Z  \n",
       "2317   255   255   255   255   255   255   255      Z  \n",
       "2318   255   255   255   255   255   255   255      Z  \n",
       "2319     0     0   255   255   255   255   255      Z  \n",
       "2320   255   255   255   255   255   255   255      Z  \n",
       "2321   255   255   255   255   255   255   255      Z  \n",
       "2322   255   255   255   255   255   255   255      Z  \n",
       "2323     0     0     0     0     0     0     0      Z  \n",
       "2324   255   255   255   255   255   255   255      Z  \n",
       "2325   255   255   255   255     0     0     0      Z  \n",
       "2326   255   255   255   255     0   255   255      Z  \n",
       "2327   255   255   255   255   255   255   255      Z  \n",
       "\n",
       "[2328 rows x 2501 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainColor = pd.read_csv('testdata_color.csv')\n",
    "trainColor_shuffle = trainColor.sample(frac=1).reset_index(drop=True)\n",
    "trainColor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['B', 'Z', 'E', ..., 'W', 'F', 'L'], dtype=object)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CNNtrain = trainColor_shuffle.drop('label', axis=1) / 255 # normalize\n",
    "CNNtrain_label = trainColor_shuffle.values[:, -1]\n",
    "CNNtrain_label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 25, 4, ..., 22, 5, 11], dtype=object)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import string\n",
    "alph = string.ascii_uppercase\n",
    "for i in range(len(CNNtrain_label)):\n",
    "    for j in range(26):\n",
    "        if CNNtrain_label[i] == alph[j]:\n",
    "            CNNtrain_label[i]=j\n",
    "CNNtrain_label\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train = CNNtrain_label.astype(int)\n",
    "one_hot_CNNtrainLabel = one_hot_encoding(train, 26)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one_hot_CNNtrainLabel[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# parameters initialization\n",
    "numberOfNodes = 5000\n",
    "batchSize = 128\n",
    "numberOfEpoch = 50\n",
    "learningRate = 0.0001\n",
    "keep_prob_rate = 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Build Neural Network graph\n",
    "numberOfClass = 26\n",
    "imageSize = (50, 50)\n",
    "features = np.prod(imageSize)\n",
    "graph = tf.Graph()\n",
    "tf.reset_default_graph()\n",
    "with graph.as_default():\n",
    "    \n",
    "    # get inputs\n",
    "    inputT, labelT, keep_prob = getInputTensor(features, numberOfClass)\n",
    "    \n",
    "    # build fully-conneted neural network\n",
    "    logits = build_nn(inputT, numberOfNodes, numberOfClass, keep_prob)\n",
    "    \n",
    "    # softmax with cross entropy\n",
    "    probability = tf.nn.softmax(logits, name = 'probability')\n",
    "    \n",
    "    # Cost\n",
    "    cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits = logits, labels = labelT))\n",
    "    \n",
    "    # optimizer\n",
    "    optimizer = tf.train.AdamOptimizer(learning_rate = learningRate).minimize(cost)\n",
    "    \n",
    "    # accuracy\n",
    "    correctPrediction = tf.equal(tf.argmax(probability, 1),tf.argmax(labelT, 1))\n",
    "    accuracy = tf.reduce_mean(tf.cast(correctPrediction, tf.float32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1/50 \tTraining Loss: 63.647 \tValidation Loss: 64.997 \tAccuracy: 3.43%\n",
      "Epoch: 2/50 \tTraining Loss: 48.990 \tValidation Loss: 51.819 \tAccuracy: 4.29%\n",
      "Epoch: 3/50 \tTraining Loss: 41.507 \tValidation Loss: 40.800 \tAccuracy: 5.29%\n",
      "Epoch: 4/50 \tTraining Loss: 36.925 \tValidation Loss: 35.480 \tAccuracy: 8.73%\n",
      "Epoch: 5/50 \tTraining Loss: 29.083 \tValidation Loss: 30.191 \tAccuracy: 10.59%\n",
      "Epoch: 6/50 \tTraining Loss: 24.620 \tValidation Loss: 26.098 \tAccuracy: 12.59%\n",
      "Epoch: 7/50 \tTraining Loss: 25.759 \tValidation Loss: 22.277 \tAccuracy: 18.74%\n",
      "Epoch: 8/50 \tTraining Loss: 17.866 \tValidation Loss: 20.556 \tAccuracy: 20.60%\n",
      "Epoch: 9/50 \tTraining Loss: 19.298 \tValidation Loss: 18.204 \tAccuracy: 24.89%\n",
      "Epoch: 10/50 \tTraining Loss: 13.209 \tValidation Loss: 15.294 \tAccuracy: 32.76%\n",
      "Epoch: 11/50 \tTraining Loss: 13.572 \tValidation Loss: 13.810 \tAccuracy: 35.19%\n",
      "Epoch: 12/50 \tTraining Loss: 14.885 \tValidation Loss: 11.991 \tAccuracy: 42.20%\n",
      "Epoch: 13/50 \tTraining Loss: 9.742 \tValidation Loss: 11.901 \tAccuracy: 42.63%\n",
      "Epoch: 14/50 \tTraining Loss: 12.258 \tValidation Loss: 10.333 \tAccuracy: 46.35%\n",
      "Epoch: 15/50 \tTraining Loss: 9.031 \tValidation Loss: 10.127 \tAccuracy: 48.07%\n",
      "Epoch: 16/50 \tTraining Loss: 9.629 \tValidation Loss: 8.218 \tAccuracy: 53.22%\n",
      "Epoch: 17/50 \tTraining Loss: 8.298 \tValidation Loss: 7.587 \tAccuracy: 54.65%\n",
      "Epoch: 18/50 \tTraining Loss: 6.318 \tValidation Loss: 6.585 \tAccuracy: 57.94%\n",
      "Epoch: 19/50 \tTraining Loss: 6.805 \tValidation Loss: 6.600 \tAccuracy: 60.80%\n",
      "Epoch: 20/50 \tTraining Loss: 6.603 \tValidation Loss: 5.497 \tAccuracy: 65.24%\n",
      "Epoch: 21/50 \tTraining Loss: 4.442 \tValidation Loss: 5.860 \tAccuracy: 64.38%\n",
      "Epoch: 22/50 \tTraining Loss: 3.569 \tValidation Loss: 4.571 \tAccuracy: 68.38%\n",
      "Epoch: 23/50 \tTraining Loss: 4.925 \tValidation Loss: 4.314 \tAccuracy: 71.53%\n",
      "Epoch: 24/50 \tTraining Loss: 3.702 \tValidation Loss: 4.051 \tAccuracy: 72.96%\n",
      "Epoch: 25/50 \tTraining Loss: 4.770 \tValidation Loss: 3.380 \tAccuracy: 75.39%\n",
      "Epoch: 26/50 \tTraining Loss: 2.226 \tValidation Loss: 3.310 \tAccuracy: 74.96%\n",
      "Epoch: 27/50 \tTraining Loss: 3.311 \tValidation Loss: 2.703 \tAccuracy: 79.69%\n",
      "Epoch: 28/50 \tTraining Loss: 2.168 \tValidation Loss: 2.259 \tAccuracy: 80.97%\n",
      "Epoch: 29/50 \tTraining Loss: 1.541 \tValidation Loss: 2.389 \tAccuracy: 81.83%\n",
      "Epoch: 30/50 \tTraining Loss: 1.523 \tValidation Loss: 2.062 \tAccuracy: 82.26%\n",
      "Epoch: 31/50 \tTraining Loss: 1.222 \tValidation Loss: 1.677 \tAccuracy: 85.41%\n",
      "Epoch: 32/50 \tTraining Loss: 2.183 \tValidation Loss: 1.366 \tAccuracy: 87.12%\n",
      "Epoch: 33/50 \tTraining Loss: 1.616 \tValidation Loss: 1.367 \tAccuracy: 87.27%\n",
      "Epoch: 34/50 \tTraining Loss: 0.965 \tValidation Loss: 1.186 \tAccuracy: 89.13%\n",
      "Epoch: 35/50 \tTraining Loss: 0.971 \tValidation Loss: 0.887 \tAccuracy: 91.70%\n",
      "Epoch: 36/50 \tTraining Loss: 0.488 \tValidation Loss: 0.865 \tAccuracy: 90.56%\n",
      "Epoch: 37/50 \tTraining Loss: 0.972 \tValidation Loss: 0.807 \tAccuracy: 92.13%\n",
      "Epoch: 38/50 \tTraining Loss: 1.033 \tValidation Loss: 0.705 \tAccuracy: 93.13%\n",
      "Epoch: 39/50 \tTraining Loss: 0.997 \tValidation Loss: 0.527 \tAccuracy: 93.71%\n",
      "Epoch: 40/50 \tTraining Loss: 0.357 \tValidation Loss: 0.387 \tAccuracy: 96.28%\n",
      "Epoch: 41/50 \tTraining Loss: 0.253 \tValidation Loss: 0.468 \tAccuracy: 95.42%\n",
      "Epoch: 42/50 \tTraining Loss: 0.429 \tValidation Loss: 0.316 \tAccuracy: 96.71%\n",
      "Epoch: 43/50 \tTraining Loss: 0.370 \tValidation Loss: 0.197 \tAccuracy: 98.00%\n",
      "Epoch: 44/50 \tTraining Loss: 0.277 \tValidation Loss: 0.193 \tAccuracy: 97.85%\n",
      "Epoch: 45/50 \tTraining Loss: 0.158 \tValidation Loss: 0.233 \tAccuracy: 97.85%\n",
      "Epoch: 46/50 \tTraining Loss: 0.171 \tValidation Loss: 0.204 \tAccuracy: 98.14%\n",
      "Epoch: 47/50 \tTraining Loss: 0.157 \tValidation Loss: 0.165 \tAccuracy: 98.57%\n",
      "Epoch: 48/50 \tTraining Loss: 0.290 \tValidation Loss: 0.108 \tAccuracy: 99.28%\n",
      "Epoch: 49/50 \tTraining Loss: 0.049 \tValidation Loss: 0.089 \tAccuracy: 99.43%\n",
      "Epoch: 50/50 \tTraining Loss: 0.121 \tValidation Loss: 0.042 \tAccuracy: 99.71%\n"
     ]
    }
   ],
   "source": [
    "with tf.Session(graph=graph) as sess:\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "    \n",
    "    for epoch in range(numberOfEpoch):\n",
    "        # training data & validation data\n",
    "        train_x, val_x, train_y, val_y = train_test_split(CNNtrain, one_hot_CNNtrainLabel,test_size = 0.3)   \n",
    "        # training loss\n",
    "        for i in range(0, len(train_x), batchSize):\n",
    "            trainLoss, _, _ = sess.run([cost, probability, optimizer], feed_dict = {\n",
    "                inputT: train_x[i: i+batchSize],\n",
    "                labelT: train_y[i: i+batchSize],\n",
    "                keep_prob: keep_prob_rate   \n",
    "            })\n",
    "            \n",
    "        # validation loss\n",
    "        valAcc, valLoss = sess.run([accuracy, cost], feed_dict ={\n",
    "            inputT: val_x,\n",
    "            labelT: val_y,\n",
    "            keep_prob: 1.0\n",
    "        })\n",
    "        \n",
    "        \n",
    "        # print out\n",
    "        printResult(epoch, numberOfEpoch, trainLoss, valLoss, valAcc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~mlu821/5.embed\" height=\"525px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import plotly.plotly as py\n",
    "import plotly.graph_objs as go\n",
    "\n",
    "\n",
    "x1 = [i for i in range(50)]\n",
    "y1 = [0.0343, 0.0429, 0.0529, 0.0873, 0.1059, 0.1259, 0.1874, 0.2060, 0.2489, 0.3276, 0.3519, 0.4220, 0.4263,\n",
    "    0.4635, 0.4807, 0.5322, 0.5465, 0.5794, 0.6080, 0.6524, 0.6438, 0.6838, 0.7153, 0.7296, 0.7539, 0.7496, 0.7969,\n",
    "    0.8097, 0.8183, 0.8226, 0.8541, 0.8712, 0.8727, 0.8913, 0.9170, 0.9056, 0.9213, 0.9313, 0.9371, 0.9628,\n",
    "    0.9542, 0.9671, 0.98, 0.9785, 0.9785, 0.9814, 0.9857, 0.9928, 0.9943, 0.9971]\n",
    "\n",
    "# Create a trace\n",
    "trace1 = go.Scatter(\n",
    "    x = x1,\n",
    "    y = y1\n",
    ")\n",
    "\n",
    "x2 = [j for j in range(40)]\n",
    "y2 = [0.0513, 0.0979, 0.1021, 0.1725, 0.2221, 0.2960, 0.3124, 0.3846, 0.4662, 0.5245, 0.5734, 0.6550, 0.7179,\n",
    "     0.7296, 0.7692, 0.7646, 0.8019, 0.8555, 0.8601, 0.8788, 0.8625, 0.8834, 0.9021, 0.9347, 0.9534, 0.9441,\n",
    "     0.9674, 0.9697, 0.9720, 0.9744, 0.9790, 0.9744, 0.9837, 0.9860, 0.9860, 0.9953, 0.9883, 0.9860, 0.9860,\n",
    "     0.9930]\n",
    "\n",
    "trace2 = go.Scatter(\n",
    "    x = x2,\n",
    "    y = y2\n",
    ")\n",
    "\n",
    "data = [trace1, trace2]\n",
    "\n",
    "py.iplot(data,filename='basic-line')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import plotly \n",
    "plotly.tools.set_credentials_file(username='mlu821', api_key='MPHbznrO8UIgyhrL4a0G')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~mlu821/5.embed\" height=\"525px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x1 = [i for i in range(50)]\n",
    "y1 = [64.997,51.819,40.800,35.480,30.191,26.098,22.277,20.556,18.204,15.294,13.810,11.991,11.901,10.333,\n",
    "      10.127,8.218,7.587,6.585,6.600,5.497,5.860,4.571,4.314,4.051,3.380,3.310,2.703,2.259,2.389,2.062,\n",
    "      1.677,1.366,1.367,1.186,0.887,0.865,0.807,0.705,0.527,0.387,0.468,0.316,0.197,0.193,0.233,0.204,0.165,\n",
    "      0.108,0.089,0.042]\n",
    "\n",
    "# Create a trace\n",
    "trace1 = go.Scatter(\n",
    "    x = x1,\n",
    "    y = y1\n",
    ")\n",
    "\n",
    "x2 = [j for j in range(40)]\n",
    "y2 = [45.760,32.736,26.668,21.867,16.470,13.141,12.247,9.449,7.488,6.032,5.457,4.322,3.126,2.606,2.019,\n",
    "      2.285,1.635,1.351,1.070,0.944,0.965,0.792,0.792,0.460,0.436, 0.456, 0.298,0.255,0.351,0.225,0.165,\n",
    "      0.219,0.122,0.118,0.190,0.053,0.127,0.060,0.101,0.078]\n",
    "\n",
    "trace2 = go.Scatter(\n",
    "    x = x2,\n",
    "    y = y2\n",
    ")\n",
    "\n",
    "data = [trace1, trace2]\n",
    "\n",
    "py.iplot(data,filename='basic-line')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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