Breast Cancer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "import keras\n",
    "import keras.callbacks as ct\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    2\n",
      "1    2\n",
      "2    2\n",
      "3    2\n",
      "4    2\n",
      "Name: class, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>clump_thickness</th>\n",
       "      <th>uniform_cell_size</th>\n",
       "      <th>uniform_cell_shape</th>\n",
       "      <th>marginal_adhesion</th>\n",
       "      <th>single_epi_cell_size</th>\n",
       "      <th>bare_nuclei</th>\n",
       "      <th>bland_chromation</th>\n",
       "      <th>normal_nucleoli</th>\n",
       "      <th>mitoses</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   clump_thickness  uniform_cell_size  uniform_cell_shape  marginal_adhesion  \\\n",
       "0                5                  1                   1                  1   \n",
       "1                5                  4                   4                  5   \n",
       "2                3                  1                   1                  1   \n",
       "3                6                  8                   8                  1   \n",
       "4                4                  1                   1                  3   \n",
       "\n",
       "   single_epi_cell_size bare_nuclei  bland_chromation  normal_nucleoli  \\\n",
       "0                     2           1                 3                1   \n",
       "1                     7          10                 3                2   \n",
       "2                     2           2                 3                1   \n",
       "3                     3           4                 3                7   \n",
       "4                     2           1                 3                1   \n",
       "\n",
       "   mitoses  \n",
       "0        1  \n",
       "1        1  \n",
       "2        1  \n",
       "3        1  \n",
       "4        1  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataframe = pd.read_csv(\"datasets.data\")\n",
    "dataframe = dataframe.drop('id', 1)\n",
    "df_label = dataframe['class']\n",
    "df_features = dataframe.drop('class', 1)\n",
    "df_features.replace('?', -99999, inplace=True)\n",
    "\n",
    "print(df_label.head())\n",
    "df_features.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "label = []\n",
    "for lab in df_label:\n",
    "    if lab == 2:\n",
    "        label.append([1, 0])  # class 2\n",
    "    elif lab == 4:\n",
    "        label.append([0, 1])  # class 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(699, 9) (699, 2)\n"
     ]
    }
   ],
   "source": [
    "data = np.array(df_features)\n",
    "label = np.array(label)\n",
    "print(data.shape,label.shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(468, 9)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(data, label, test_size=0.33, random_state=42)\n",
    "x_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 699 samples, validate on 231 samples\n",
      "Epoch 1/1000\n",
      "699/699 [==============================] - 0s - loss: 0.2518 - acc: 0.5851 - val_loss: 0.1582 - val_acc: 0.8225\n",
      "Epoch 2/1000\n",
      "699/699 [==============================] - 0s - loss: 0.1419 - acc: 0.8069 - val_loss: 0.1361 - val_acc: 0.8095\n",
      "Epoch 3/1000\n",
      "699/699 [==============================] - 0s - loss: 0.1166 - acc: 0.8312 - val_loss: 0.1052 - val_acc: 0.8528\n",
      "Epoch 4/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0922 - acc: 0.8898 - val_loss: 0.0934 - val_acc: 0.9004\n",
      "Epoch 5/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0814 - acc: 0.9027 - val_loss: 0.0824 - val_acc: 0.9048\n",
      "Epoch 6/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0730 - acc: 0.9127 - val_loss: 0.0758 - val_acc: 0.9091\n",
      "Epoch 7/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0674 - acc: 0.9185 - val_loss: 0.0703 - val_acc: 0.9221\n",
      "Epoch 8/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0626 - acc: 0.9256 - val_loss: 0.0661 - val_acc: 0.9307\n",
      "Epoch 9/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0588 - acc: 0.9328 - val_loss: 0.0626 - val_acc: 0.9307\n",
      "Epoch 10/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0556 - acc: 0.9313 - val_loss: 0.0596 - val_acc: 0.9351\n",
      "Epoch 11/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0525 - acc: 0.9413 - val_loss: 0.0570 - val_acc: 0.9351\n",
      "Epoch 12/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0500 - acc: 0.9371 - val_loss: 0.0547 - val_acc: 0.9437\n",
      "Epoch 13/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0478 - acc: 0.9442 - val_loss: 0.0522 - val_acc: 0.9437\n",
      "Epoch 14/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0457 - acc: 0.9485 - val_loss: 0.0503 - val_acc: 0.9481\n",
      "Epoch 15/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0438 - acc: 0.9514 - val_loss: 0.0486 - val_acc: 0.9481\n",
      "Epoch 16/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0421 - acc: 0.9542 - val_loss: 0.0470 - val_acc: 0.9481\n",
      "Epoch 17/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0406 - acc: 0.9557 - val_loss: 0.0458 - val_acc: 0.9481\n",
      "Epoch 18/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0390 - acc: 0.9557 - val_loss: 0.0443 - val_acc: 0.9524\n",
      "Epoch 19/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0377 - acc: 0.9599 - val_loss: 0.0429 - val_acc: 0.9524\n",
      "Epoch 20/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0365 - acc: 0.9614 - val_loss: 0.0418 - val_acc: 0.9524\n",
      "Epoch 21/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0352 - acc: 0.9628 - val_loss: 0.0405 - val_acc: 0.9567\n",
      "Epoch 22/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0340 - acc: 0.9671 - val_loss: 0.0396 - val_acc: 0.9567\n",
      "Epoch 23/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0332 - acc: 0.9657 - val_loss: 0.0386 - val_acc: 0.9567\n",
      "Epoch 24/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0321 - acc: 0.9657 - val_loss: 0.0376 - val_acc: 0.9567\n",
      "Epoch 25/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0313 - acc: 0.9671 - val_loss: 0.0366 - val_acc: 0.9610\n",
      "Epoch 26/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0304 - acc: 0.9714 - val_loss: 0.0357 - val_acc: 0.9654\n",
      "Epoch 27/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0298 - acc: 0.9728 - val_loss: 0.0349 - val_acc: 0.9654\n",
      "Epoch 28/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0291 - acc: 0.9742 - val_loss: 0.0342 - val_acc: 0.9654\n",
      "Epoch 29/1000\n",
      "699/699 [==============================] - ETA: 0s - loss: 0.0177 - acc: 0.985 - 0s - loss: 0.0279 - acc: 0.9714 - val_loss: 0.0334 - val_acc: 0.9654\n",
      "Epoch 30/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0277 - acc: 0.9742 - val_loss: 0.0327 - val_acc: 0.9654\n",
      "Epoch 31/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0269 - acc: 0.9714 - val_loss: 0.0322 - val_acc: 0.9654\n",
      "Epoch 32/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0264 - acc: 0.9742 - val_loss: 0.0314 - val_acc: 0.9654\n",
      "Epoch 33/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0258 - acc: 0.9728 - val_loss: 0.0308 - val_acc: 0.9654\n",
      "Epoch 34/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0251 - acc: 0.9728 - val_loss: 0.0303 - val_acc: 0.9654\n",
      "Epoch 35/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0247 - acc: 0.9728 - val_loss: 0.0298 - val_acc: 0.9654\n",
      "Epoch 36/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0243 - acc: 0.9728 - val_loss: 0.0293 - val_acc: 0.9654\n",
      "Epoch 37/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0237 - acc: 0.9757 - val_loss: 0.0288 - val_acc: 0.9697\n",
      "Epoch 38/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0235 - acc: 0.9742 - val_loss: 0.0283 - val_acc: 0.9697\n",
      "Epoch 39/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0230 - acc: 0.9785 - val_loss: 0.0279 - val_acc: 0.9697\n",
      "Epoch 40/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0226 - acc: 0.9771 - val_loss: 0.0275 - val_acc: 0.9697\n",
      "Epoch 41/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0221 - acc: 0.9771 - val_loss: 0.0271 - val_acc: 0.9697\n",
      "Epoch 42/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0218 - acc: 0.9771 - val_loss: 0.0268 - val_acc: 0.9697\n",
      "Epoch 43/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0215 - acc: 0.9771 - val_loss: 0.0263 - val_acc: 0.9697\n",
      "Epoch 44/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0211 - acc: 0.9785 - val_loss: 0.0260 - val_acc: 0.9697\n",
      "Epoch 45/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0206 - acc: 0.9785 - val_loss: 0.0259 - val_acc: 0.9697\n",
      "Epoch 46/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0205 - acc: 0.9800 - val_loss: 0.0254 - val_acc: 0.9697\n",
      "Epoch 47/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0201 - acc: 0.9785 - val_loss: 0.0250 - val_acc: 0.9697\n",
      "Epoch 48/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0200 - acc: 0.9785 - val_loss: 0.0247 - val_acc: 0.9697\n",
      "Epoch 49/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0195 - acc: 0.9785 - val_loss: 0.0245 - val_acc: 0.9697\n",
      "Epoch 50/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0197 - acc: 0.9785 - val_loss: 0.0243 - val_acc: 0.9697\n",
      "Epoch 51/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0196 - acc: 0.9800 - val_loss: 0.0239 - val_acc: 0.9697\n",
      "Epoch 52/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0198 - acc: 0.9828 - val_loss: 0.0239 - val_acc: 0.9740\n",
      "Epoch 53/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0186 - acc: 0.9800 - val_loss: 0.0237 - val_acc: 0.9697\n",
      "Epoch 54/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0187 - acc: 0.9800 - val_loss: 0.0236 - val_acc: 0.9784\n",
      "Epoch 55/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0183 - acc: 0.9843 - val_loss: 0.0230 - val_acc: 0.9697\n",
      "Epoch 56/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0185 - acc: 0.9800 - val_loss: 0.0230 - val_acc: 0.9697\n",
      "Epoch 57/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0181 - acc: 0.9828 - val_loss: 0.0232 - val_acc: 0.9784\n",
      "Epoch 58/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0179 - acc: 0.9814 - val_loss: 0.0227 - val_acc: 0.9697\n",
      "Epoch 59/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0178 - acc: 0.9814 - val_loss: 0.0223 - val_acc: 0.9784\n",
      "Epoch 60/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0176 - acc: 0.9843 - val_loss: 0.0220 - val_acc: 0.9784\n",
      "Epoch 61/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0174 - acc: 0.9814 - val_loss: 0.0216 - val_acc: 0.9740\n",
      "Epoch 62/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0171 - acc: 0.9843 - val_loss: 0.0218 - val_acc: 0.9784\n",
      "Epoch 63/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0172 - acc: 0.9843 - val_loss: 0.0213 - val_acc: 0.9740\n",
      "Epoch 64/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0174 - acc: 0.9814 - val_loss: 0.0213 - val_acc: 0.9740\n",
      "Epoch 65/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "699/699 [==============================] - 0s - loss: 0.0194 - acc: 0.9828 - val_loss: 0.0210 - val_acc: 0.9784\n",
      "Epoch 66/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0181 - acc: 0.9785 - val_loss: 0.0212 - val_acc: 0.9740\n",
      "Epoch 67/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0168 - acc: 0.9843 - val_loss: 0.0215 - val_acc: 0.9784\n",
      "Epoch 68/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0165 - acc: 0.9843 - val_loss: 0.0205 - val_acc: 0.9784\n",
      "Epoch 69/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0164 - acc: 0.9828 - val_loss: 0.0208 - val_acc: 0.9784\n",
      "Epoch 70/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0162 - acc: 0.9843 - val_loss: 0.0204 - val_acc: 0.9784\n",
      "Epoch 71/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0159 - acc: 0.9843 - val_loss: 0.0202 - val_acc: 0.9784\n",
      "Epoch 72/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0160 - acc: 0.9843 - val_loss: 0.0201 - val_acc: 0.9784\n",
      "Epoch 73/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0157 - acc: 0.9843 - val_loss: 0.0199 - val_acc: 0.9784\n",
      "Epoch 74/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0160 - acc: 0.9814 - val_loss: 0.0196 - val_acc: 0.9784\n",
      "Epoch 75/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0155 - acc: 0.9843 - val_loss: 0.0199 - val_acc: 0.9784\n",
      "Epoch 76/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0161 - acc: 0.9843 - val_loss: 0.0193 - val_acc: 0.9827\n",
      "Epoch 77/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0156 - acc: 0.9857 - val_loss: 0.0198 - val_acc: 0.9784\n",
      "Epoch 78/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0157 - acc: 0.9843 - val_loss: 0.0191 - val_acc: 0.9827\n",
      "Epoch 79/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0152 - acc: 0.9857 - val_loss: 0.0191 - val_acc: 0.9784\n",
      "Epoch 80/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0150 - acc: 0.9843 - val_loss: 0.0189 - val_acc: 0.9784\n",
      "Epoch 81/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0150 - acc: 0.9843 - val_loss: 0.0187 - val_acc: 0.9784\n",
      "Epoch 82/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0148 - acc: 0.9843 - val_loss: 0.0188 - val_acc: 0.9784\n",
      "Epoch 83/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0146 - acc: 0.9857 - val_loss: 0.0183 - val_acc: 0.9827\n",
      "Epoch 84/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0147 - acc: 0.9843 - val_loss: 0.0184 - val_acc: 0.9784\n",
      "Epoch 85/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0149 - acc: 0.9857 - val_loss: 0.0182 - val_acc: 0.9827\n",
      "Epoch 86/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0150 - acc: 0.9843 - val_loss: 0.0185 - val_acc: 0.9784\n",
      "Epoch 87/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0159 - acc: 0.9800 - val_loss: 0.0178 - val_acc: 0.9827\n",
      "Epoch 88/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0147 - acc: 0.9857 - val_loss: 0.0193 - val_acc: 0.9784\n",
      "Epoch 89/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0143 - acc: 0.9857 - val_loss: 0.0177 - val_acc: 0.9827\n",
      "Epoch 90/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0140 - acc: 0.9857 - val_loss: 0.0186 - val_acc: 0.9784\n",
      "Epoch 91/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0138 - acc: 0.9843 - val_loss: 0.0175 - val_acc: 0.9827\n",
      "Epoch 92/1000\n",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     ]
    },
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      "Epoch 252/1000\n",
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      "Epoch 253/1000\n",
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      "Epoch 254/1000\n",
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      "Epoch 255/1000\n",
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      "Epoch 256/1000\n",
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      "Epoch 257/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "699/699 [==============================] - 0s - loss: 0.0040 - acc: 0.9971 - val_loss: 0.0088 - val_acc: 0.9913\n",
      "Epoch 258/1000\n",
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      "Epoch 321/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "699/699 [==============================] - 0s - loss: 0.0030 - acc: 0.9971 - val_loss: 0.0074 - val_acc: 0.9913\n",
      "Epoch 322/1000\n",
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      "Epoch 383/1000\n",
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      "Epoch 385/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "Epoch 449/1000\n"
     ]
    },
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     "text": [
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      "Epoch 505/1000\n",
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      "Epoch 506/1000\n",
      "699/699 [==============================] - ETA: 0s - loss: 1.2932e-04 - acc: 1.000 - 0s - loss: 0.0029 - acc: 0.9971 - val_loss: 0.0087 - val_acc: 0.9913\n",
      "Epoch 507/1000\n",
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      "Epoch 508/1000\n",
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      "Epoch 509/1000\n",
      "699/699 [==============================] - ETA: 0s - loss: 6.3926e-05 - acc: 1.000 - 0s - loss: 0.0029 - acc: 0.9971 - val_loss: 0.0087 - val_acc: 0.9913\n",
      "Epoch 510/1000\n",
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      "Epoch 511/1000\n",
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      "Epoch 512/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "Epoch 513/1000\n",
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      "Epoch 525/1000\n",
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      "Epoch 528/1000\n",
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      "Epoch 535/1000\n",
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      "Epoch 576/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "Epoch 577/1000\n",
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      "Epoch 599/1000\n",
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      "Epoch 600/1000\n",
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      "Epoch 601/1000\n",
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      "Epoch 602/1000\n",
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      "Epoch 604/1000\n",
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      "Epoch 608/1000\n",
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      "Epoch 609/1000\n",
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      "Epoch 610/1000\n",
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      "Epoch 613/1000\n",
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      "Epoch 617/1000\n",
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      "Epoch 618/1000\n",
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      "Epoch 619/1000\n",
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      "Epoch 621/1000\n",
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      "Epoch 622/1000\n",
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      "Epoch 623/1000\n",
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      "Epoch 625/1000\n",
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      "Epoch 626/1000\n",
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      "Epoch 627/1000\n",
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      "Epoch 628/1000\n",
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      "Epoch 629/1000\n",
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      "Epoch 634/1000\n",
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      "Epoch 635/1000\n",
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      "Epoch 636/1000\n",
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      "Epoch 637/1000\n",
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      "Epoch 638/1000\n",
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      "Epoch 639/1000\n",
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      "Epoch 640/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "Epoch 641/1000\n",
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      "Epoch 644/1000\n",
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      "Epoch 651/1000\n",
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      "Epoch 652/1000\n",
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      "Epoch 653/1000\n",
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      "Epoch 655/1000\n",
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      "Epoch 656/1000\n",
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      "Epoch 657/1000\n",
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      "Epoch 659/1000\n",
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      "Epoch 660/1000\n",
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      "Epoch 661/1000\n",
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      "Epoch 662/1000\n",
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      "Epoch 663/1000\n",
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      "Epoch 664/1000\n",
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      "Epoch 665/1000\n",
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      "Epoch 669/1000\n",
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      "Epoch 670/1000\n",
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      "Epoch 673/1000\n",
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      "Epoch 676/1000\n",
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      "Epoch 693/1000\n",
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      "Epoch 699/1000\n",
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      "Epoch 700/1000\n",
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      "Epoch 701/1000\n",
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      "Epoch 702/1000\n",
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      "Epoch 703/1000\n",
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      "Epoch 704/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "699/699 [==============================] - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 705/1000\n",
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      "Epoch 708/1000\n",
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      "Epoch 709/1000\n",
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      "Epoch 710/1000\n",
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      "Epoch 711/1000\n",
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      "Epoch 712/1000\n",
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      "Epoch 713/1000\n",
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      "Epoch 715/1000\n",
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      "Epoch 717/1000\n",
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      "Epoch 718/1000\n",
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      "Epoch 719/1000\n",
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      "Epoch 720/1000\n",
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      "Epoch 721/1000\n",
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      "Epoch 722/1000\n",
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      "Epoch 723/1000\n",
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      "Epoch 724/1000\n",
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      "Epoch 725/1000\n",
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      "Epoch 726/1000\n",
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      "Epoch 727/1000\n",
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      "Epoch 728/1000\n",
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      "Epoch 729/1000\n",
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      "Epoch 730/1000\n",
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      "Epoch 731/1000\n",
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      "Epoch 732/1000\n",
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      "Epoch 733/1000\n",
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      "Epoch 734/1000\n",
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      "Epoch 735/1000\n",
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      "Epoch 736/1000\n",
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      "Epoch 737/1000\n",
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      "Epoch 738/1000\n",
      "699/699 [==============================] - ETA: 0s - loss: 1.9989e-04 - acc: 1.000 - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 739/1000\n",
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      "Epoch 740/1000\n",
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      "Epoch 741/1000\n",
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      "Epoch 742/1000\n",
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      "Epoch 743/1000\n",
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      "Epoch 744/1000\n",
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      "Epoch 745/1000\n",
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      "Epoch 746/1000\n",
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      "Epoch 747/1000\n",
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      "Epoch 748/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 749/1000\n",
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      "Epoch 750/1000\n",
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      "Epoch 751/1000\n",
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      "Epoch 752/1000\n",
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      "Epoch 753/1000\n",
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      "Epoch 754/1000\n",
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      "Epoch 755/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 756/1000\n",
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      "Epoch 757/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 758/1000\n",
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      "Epoch 759/1000\n",
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      "Epoch 760/1000\n",
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      "Epoch 761/1000\n",
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      "Epoch 762/1000\n",
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      "Epoch 763/1000\n",
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      "Epoch 764/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 765/1000\n",
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      "Epoch 766/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 767/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 768/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "Epoch 769/1000\n",
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      "Epoch 774/1000\n",
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      "Epoch 778/1000\n",
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      "Epoch 780/1000\n",
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      "Epoch 781/1000\n",
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      "Epoch 782/1000\n",
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      "Epoch 783/1000\n",
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      "Epoch 784/1000\n",
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      "Epoch 785/1000\n",
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      "Epoch 786/1000\n",
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      "Epoch 787/1000\n",
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      "Epoch 788/1000\n",
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      "Epoch 789/1000\n",
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      "Epoch 790/1000\n",
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      "Epoch 791/1000\n",
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      "Epoch 792/1000\n",
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      "Epoch 793/1000\n",
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      "Epoch 794/1000\n",
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      "Epoch 795/1000\n",
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      "Epoch 796/1000\n",
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      "Epoch 797/1000\n",
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      "Epoch 798/1000\n",
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      "Epoch 799/1000\n",
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      "Epoch 800/1000\n",
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      "Epoch 801/1000\n",
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      "Epoch 802/1000\n",
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      "Epoch 803/1000\n",
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      "Epoch 804/1000\n",
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      "Epoch 808/1000\n",
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      "Epoch 816/1000\n",
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      "Epoch 818/1000\n",
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      "Epoch 819/1000\n",
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      "Epoch 820/1000\n",
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      "Epoch 821/1000\n",
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      "Epoch 822/1000\n",
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      "Epoch 827/1000\n",
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      "Epoch 828/1000\n",
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      "Epoch 829/1000\n",
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      "Epoch 830/1000\n",
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      "Epoch 831/1000\n",
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      "Epoch 832/1000\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 833/1000\n",
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      "Epoch 834/1000\n",
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      "Epoch 835/1000\n",
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      "Epoch 836/1000\n",
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      "Epoch 837/1000\n",
      "699/699 [==============================] - ETA: 0s - loss: 2.5665e-04 - acc: 1.000 - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 838/1000\n",
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      "Epoch 839/1000\n",
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      "Epoch 840/1000\n",
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      "Epoch 842/1000\n",
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      "Epoch 843/1000\n",
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      "Epoch 844/1000\n",
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      "Epoch 845/1000\n",
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      "Epoch 846/1000\n",
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      "Epoch 847/1000\n",
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      "Epoch 848/1000\n",
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      "Epoch 849/1000\n",
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      "Epoch 850/1000\n",
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      "Epoch 851/1000\n",
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      "Epoch 852/1000\n",
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      "Epoch 853/1000\n",
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      "Epoch 854/1000\n",
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      "Epoch 855/1000\n",
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      "Epoch 856/1000\n",
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      "Epoch 857/1000\n",
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      "Epoch 858/1000\n",
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      "Epoch 859/1000\n",
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      "Epoch 860/1000\n",
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      "Epoch 861/1000\n",
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      "Epoch 862/1000\n",
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      "Epoch 863/1000\n",
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      "Epoch 864/1000\n",
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      "Epoch 865/1000\n",
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      "Epoch 866/1000\n",
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      "Epoch 867/1000\n",
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      "Epoch 868/1000\n",
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      "Epoch 869/1000\n",
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      "Epoch 870/1000\n",
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      "Epoch 871/1000\n",
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      "Epoch 872/1000\n",
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      "Epoch 873/1000\n",
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      "Epoch 874/1000\n",
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      "Epoch 875/1000\n",
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      "Epoch 876/1000\n",
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      "Epoch 877/1000\n",
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      "Epoch 878/1000\n",
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      "Epoch 879/1000\n",
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      "Epoch 880/1000\n",
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      "Epoch 881/1000\n",
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      "Epoch 882/1000\n",
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      "Epoch 883/1000\n",
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      "Epoch 884/1000\n",
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      "Epoch 885/1000\n",
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      "Epoch 886/1000\n",
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      "Epoch 887/1000\n",
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      "Epoch 888/1000\n",
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      "Epoch 889/1000\n",
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      "Epoch 890/1000\n",
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      "Epoch 891/1000\n",
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      "Epoch 892/1000\n",
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      "Epoch 893/1000\n",
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      "Epoch 894/1000\n",
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      "Epoch 895/1000\n",
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      "Epoch 896/1000\n"
     ]
    },
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     "text": [
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 897/1000\n",
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      "Epoch 898/1000\n",
      "699/699 [==============================] - ETA: 0s - loss: 4.2848e-04 - acc: 1.000 - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 899/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 900/1000\n",
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      "Epoch 901/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 902/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 903/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 904/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 905/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 906/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 907/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 908/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 909/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 910/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 911/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 912/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 913/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 914/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 915/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 916/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 917/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 918/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 919/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 920/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 921/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 922/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 923/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 924/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 925/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 926/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 927/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 928/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 929/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 930/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 931/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 932/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 933/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 934/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 935/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 936/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 937/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 938/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 939/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 940/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 941/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 942/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 943/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 944/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 945/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 946/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 947/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 948/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 949/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 950/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 951/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 952/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 953/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 954/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 955/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 956/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 957/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 958/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 959/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 960/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 961/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 962/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 963/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0026 - acc: 0.9971 - val_loss: 0.0073 - val_acc: 0.9913\n",
      "Epoch 964/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 965/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 966/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 967/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 968/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 969/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 970/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 971/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 972/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 973/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 974/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 975/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 976/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 977/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 978/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 979/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 980/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 981/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 982/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 983/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 984/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 985/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 986/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 987/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 988/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 989/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0071 - val_acc: 0.9913\n",
      "Epoch 990/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 991/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 992/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 993/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 994/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 995/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 996/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 997/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 998/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 999/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n",
      "Epoch 1000/1000\n",
      "699/699 [==============================] - 0s - loss: 0.0025 - acc: 0.9971 - val_loss: 0.0072 - val_acc: 0.9913\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x11e82d5f8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = Sequential()\n",
    "model.add(Dense(48, input_dim=9, activation='tanh'))\n",
    "model.add(Dense(16, activation='tanh'))\n",
    "model.add(Dense(2, activation='softmax'))\n",
    "tbCallBack = keras.callbacks.TensorBoard(log_dir='/tmp/tflearn_logs/', histogram_freq=0, write_graph=True,\n",
    "                                         write_images=False, embeddings_freq=0, embeddings_layer_names=None,\n",
    "                                         embeddings_metadata=None)\n",
    "model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])\n",
    "model.fit(data, label, epochs=1000, batch_size=70, validation_data=(x_test, y_test), callbacks=[tbCallBack])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "231/231 [==============================] - 0s\n",
      "[0.0071887429803609848, 0.99134200811386108]\n"
     ]
    }
   ],
   "source": [
    "score = model.evaluate(x_test, y_test,batch_size=700)\n",
    "print(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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    "version": 3
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   "file_extension": ".py",
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