wine_classfication.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# [分類:Classfication]\n",
    "# ワインデータ CSV ファイルをあつかっていく"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# CSV 読み込み\n",
    "df = pd.read_csv('wine_class.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Class  Alcohol   Ash  Alcalinity of ash  Magnesium  Total phenols  \\\n",
      "0        1    14.23  2.43               15.6        127           2.80   \n",
      "1        1    13.20  2.14               11.2        100           2.65   \n",
      "2        1    13.16  2.67               18.6        101           2.80   \n",
      "3        1    14.37  2.50               16.8        113           3.85   \n",
      "4        1    13.24  2.87               21.0        118           2.80   \n",
      "5        1    14.20  2.45               15.2        112           3.27   \n",
      "6        1    14.39  2.45               14.6         96           2.50   \n",
      "7        1    14.06  2.61               17.6        121           2.60   \n",
      "8        1    14.83  2.17               14.0         97           2.80   \n",
      "9        1    13.86  2.27               16.0         98           2.98   \n",
      "10       1    14.10  2.30               18.0        105           2.95   \n",
      "11       1    14.12  2.32               16.8         95           2.20   \n",
      "12       1    13.75  2.41               16.0         89           2.60   \n",
      "13       1    14.75  2.39               11.4         91           3.10   \n",
      "14       1    14.38  2.38               12.0        102           3.30   \n",
      "15       1    13.63  2.70               17.2        112           2.85   \n",
      "16       1    14.30  2.72               20.0        120           2.80   \n",
      "17       1    13.83  2.62               20.0        115           2.95   \n",
      "18       1    14.19  2.48               16.5        108           3.30   \n",
      "19       1    13.64  2.56               15.2        116           2.70   \n",
      "20       1    14.06  2.28               16.0        126           3.00   \n",
      "21       1    12.93  2.65               18.6        102           2.41   \n",
      "22       1    13.71  2.36               16.6        101           2.61   \n",
      "23       1    12.85  2.52               17.8         95           2.48   \n",
      "24       1    13.50  2.61               20.0         96           2.53   \n",
      "25       1    13.05  3.22               25.0        124           2.63   \n",
      "26       1    13.39  2.62               16.1         93           2.85   \n",
      "27       1    13.30  2.14               17.0         94           2.40   \n",
      "28       1    13.87  2.80               19.4        107           2.95   \n",
      "29       1    14.02  2.21               16.0         96           2.65   \n",
      "..     ...      ...   ...                ...        ...            ...   \n",
      "148      3    13.32  2.38               21.5         92           1.93   \n",
      "149      3    13.08  2.36               21.5        113           1.41   \n",
      "150      3    13.50  2.62               24.0        123           1.40   \n",
      "151      3    12.79  2.48               22.0        112           1.48   \n",
      "152      3    13.11  2.75               25.5        116           2.20   \n",
      "153      3    13.23  2.28               18.5         98           1.80   \n",
      "154      3    12.58  2.10               20.0        103           1.48   \n",
      "155      3    13.17  2.32               22.0         93           1.74   \n",
      "156      3    13.84  2.38               19.5         89           1.80   \n",
      "157      3    12.45  2.64               27.0         97           1.90   \n",
      "158      3    14.34  2.70               25.0         98           2.80   \n",
      "159      3    13.48  2.64               22.5         89           2.60   \n",
      "160      3    12.36  2.38               21.0         88           2.30   \n",
      "161      3    13.69  2.54               20.0        107           1.83   \n",
      "162      3    12.85  2.58               22.0        106           1.65   \n",
      "163      3    12.96  2.35               18.5        106           1.39   \n",
      "164      3    13.78  2.30               22.0         90           1.35   \n",
      "165      3    13.73  2.26               22.5         88           1.28   \n",
      "166      3    13.45  2.60               23.0        111           1.70   \n",
      "167      3    12.82  2.30               19.5         88           1.48   \n",
      "168      3    13.58  2.69               24.5        105           1.55   \n",
      "169      3    13.40  2.86               25.0        112           1.98   \n",
      "170      3    12.20  2.32               19.0         96           1.25   \n",
      "171      3    12.77  2.28               19.5         86           1.39   \n",
      "172      3    14.16  2.48               20.0         91           1.68   \n",
      "173      3    13.71  2.45               20.5         95           1.68   \n",
      "174      3    13.40  2.48               23.0        102           1.80   \n",
      "175      3    13.27  2.26               20.0        120           1.59   \n",
      "176      3    13.17  2.37               20.0        120           1.65   \n",
      "177      3    14.13  2.74               24.5         96           2.05   \n",
      "\n",
      "     Flavanoids  Nonflavanoid phenols  Color intensity   Hue  Proline  \n",
      "0          3.06                  0.28         5.640000  1.04     1065  \n",
      "1          2.76                  0.26         4.380000  1.05     1050  \n",
      "2          3.24                  0.30         5.680000  1.03     1185  \n",
      "3          3.49                  0.24         7.800000  0.86     1480  \n",
      "4          2.69                  0.39         4.320000  1.04      735  \n",
      "5          3.39                  0.34         6.750000  1.05     1450  \n",
      "6          2.52                  0.30         5.250000  1.02     1290  \n",
      "7          2.51                  0.31         5.050000  1.06     1295  \n",
      "8          2.98                  0.29         5.200000  1.08     1045  \n",
      "9          3.15                  0.22         7.220000  1.01     1045  \n",
      "10         3.32                  0.22         5.750000  1.25     1510  \n",
      "11         2.43                  0.26         5.000000  1.17     1280  \n",
      "12         2.76                  0.29         5.600000  1.15     1320  \n",
      "13         3.69                  0.43         5.400000  1.25     1150  \n",
      "14         3.64                  0.29         7.500000  1.20     1547  \n",
      "15         2.91                  0.30         7.300000  1.28     1310  \n",
      "16         3.14                  0.33         6.200000  1.07     1280  \n",
      "17         3.40                  0.40         6.600000  1.13     1130  \n",
      "18         3.93                  0.32         8.700000  1.23     1680  \n",
      "19         3.03                  0.17         5.100000  0.96      845  \n",
      "20         3.17                  0.24         5.650000  1.09      780  \n",
      "21         2.41                  0.25         4.500000  1.03      770  \n",
      "22         2.88                  0.27         3.800000  1.11     1035  \n",
      "23         2.37                  0.26         3.930000  1.09     1015  \n",
      "24         2.61                  0.28         3.520000  1.12      845  \n",
      "25         2.68                  0.47         3.580000  1.13      830  \n",
      "26         2.94                  0.34         4.800000  0.92     1195  \n",
      "27         2.19                  0.27         3.950000  1.02     1285  \n",
      "28         2.97                  0.37         4.500000  1.25      915  \n",
      "29         2.33                  0.26         4.700000  1.04     1035  \n",
      "..          ...                   ...              ...   ...      ...  \n",
      "148        0.76                  0.45         8.420000  0.55      650  \n",
      "149        1.39                  0.34         9.400000  0.57      550  \n",
      "150        1.57                  0.22         8.600000  0.59      500  \n",
      "151        1.36                  0.24        10.800000  0.48      480  \n",
      "152        1.28                  0.26         7.100000  0.61      425  \n",
      "153        0.83                  0.61        10.520000  0.56      675  \n",
      "154        0.58                  0.53         7.600000  0.58      640  \n",
      "155        0.63                  0.61         7.900000  0.60      725  \n",
      "156        0.83                  0.48         9.010000  0.57      480  \n",
      "157        0.58                  0.63         7.500000  0.67      880  \n",
      "158        1.31                  0.53        13.000000  0.57      660  \n",
      "159        1.10                  0.52        11.750000  0.57      620  \n",
      "160        0.92                  0.50         7.650000  0.56      520  \n",
      "161        0.56                  0.50         5.880000  0.96      680  \n",
      "162        0.60                  0.60         5.580000  0.87      570  \n",
      "163        0.70                  0.40         5.280000  0.68      675  \n",
      "164        0.68                  0.41         9.580000  0.70      615  \n",
      "165        0.47                  0.52         6.620000  0.78      520  \n",
      "166        0.92                  0.43        10.680000  0.85      695  \n",
      "167        0.66                  0.40        10.260000  0.72      685  \n",
      "168        0.84                  0.39         8.660000  0.74      750  \n",
      "169        0.96                  0.27         8.500000  0.67      630  \n",
      "170        0.49                  0.40         5.500000  0.66      510  \n",
      "171        0.51                  0.48         9.899999  0.57      470  \n",
      "172        0.70                  0.44         9.700000  0.62      660  \n",
      "173        0.61                  0.52         7.700000  0.64      740  \n",
      "174        0.75                  0.43         7.300000  0.70      750  \n",
      "175        0.69                  0.43        10.200000  0.59      835  \n",
      "176        0.68                  0.53         9.300000  0.60      840  \n",
      "177        0.76                  0.56         9.200000  0.61      560  \n",
      "\n",
      "[178 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\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>Class</th>\n",
       "      <th>Alcohol</th>\n",
       "      <th>Ash</th>\n",
       "      <th>Alcalinity of ash</th>\n",
       "      <th>Magnesium</th>\n",
       "      <th>Total phenols</th>\n",
       "      <th>Flavanoids</th>\n",
       "      <th>Nonflavanoid phenols</th>\n",
       "      <th>Color intensity</th>\n",
       "      <th>Hue</th>\n",
       "      <th>Proline</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>14.23</td>\n",
       "      <td>2.43</td>\n",
       "      <td>15.6</td>\n",
       "      <td>127</td>\n",
       "      <td>2.80</td>\n",
       "      <td>3.06</td>\n",
       "      <td>0.28</td>\n",
       "      <td>5.64</td>\n",
       "      <td>1.04</td>\n",
       "      <td>1065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>13.20</td>\n",
       "      <td>2.14</td>\n",
       "      <td>11.2</td>\n",
       "      <td>100</td>\n",
       "      <td>2.65</td>\n",
       "      <td>2.76</td>\n",
       "      <td>0.26</td>\n",
       "      <td>4.38</td>\n",
       "      <td>1.05</td>\n",
       "      <td>1050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>13.16</td>\n",
       "      <td>2.67</td>\n",
       "      <td>18.6</td>\n",
       "      <td>101</td>\n",
       "      <td>2.80</td>\n",
       "      <td>3.24</td>\n",
       "      <td>0.30</td>\n",
       "      <td>5.68</td>\n",
       "      <td>1.03</td>\n",
       "      <td>1185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Class  Alcohol   Ash  Alcalinity of ash  Magnesium  Total phenols  \\\n",
       "0      1    14.23  2.43               15.6        127           2.80   \n",
       "1      1    13.20  2.14               11.2        100           2.65   \n",
       "2      1    13.16  2.67               18.6        101           2.80   \n",
       "\n",
       "   Flavanoids  Nonflavanoid phenols  Color intensity   Hue  Proline  \n",
       "0        3.06                  0.28             5.64  1.04     1065  \n",
       "1        2.76                  0.26             4.38  1.05     1050  \n",
       "2        3.24                  0.30             5.68  1.03     1185  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df\n",
    "df.head(3) # 頭から3行とりあえず表示した"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# numpyの形式にすることに注意(valuesをつける！)\n",
    "_t = df.iloc[:,0].values -1  # Class列を抽出\n",
    "_x = df.iloc[:,1:].values # 自分はClass以降の列ぜ～んぶつかうぜ！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# いつものように変換をしてあげる\n",
    "t = np.array(_t, dtype=np.int32)\n",
    "x = np.array(_x, dtype=np.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# dataset\n",
    "dataset = list(zip(x, t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from chainer.datasets import split_dataset_random\n",
    "\n",
    "n_train = int( len(dataset) * 0.7 )\n",
    "train, test = split_dataset_random(dataset, n_train, seed=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### にゅーらるねっとわ～く"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import chainer\n",
    "import chainer.links as L\n",
    "import chainer.functions as F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# MLP: Multi-layer Perceptron\n",
    "class MLP(chainer.Chain):\n",
    "    \n",
    "    def __init__(self, n_units1, n_units2, n_output):\n",
    "        super().__init__()\n",
    "        with self.init_scope():\n",
    "            self.l1 = L.Linear(None, n_units1)\n",
    "            self.l2 = L.Linear(None, n_units2)\n",
    "            self.l3 = L.Linear(None, n_output)\n",
    "            \n",
    "    # chainerは分類でsoftmax関数明記しなくてよいってマジかよ。。\n",
    "    def __call__(self, x):\n",
    "        h1 = F.relu(self.l1(x))\n",
    "        h2 = F.relu(self.l2(h1))\n",
    "        return self.l3(h2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "np.random.seed(1) # 乱数のシードを固定\n",
    "\n",
    "n_units1, n_units2, n_output = 10, 10, 3\n",
    "mlp     = MLP(n_units1, n_units2, n_output) # 分類の時だけこんなの用意してくれてる。。\n",
    "model = L.Classifier(mlp)  # 分類の時だけ手厚い。。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "optimizer = chainer.optimizers.Adam()\n",
    "optimizer.setup(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# iteratorsの設定\n",
    "batchsize = 20 # データ少ないから20で良いか 本来は100ぐらいが良さそうかな\n",
    "train_iter = chainer.iterators.SerialIterator(train, batchsize)\n",
    "test_iter = chainer.iterators.SerialIterator(test, batchsize, repeat=False, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# updaterの設定\n",
    "from chainer import training\n",
    "updater = training.StandardUpdater(train_iter, optimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# trainerとそのextensionsの設定\n",
    "from chainer.training import extensions\n",
    "\n",
    "# trainerの基本設定\n",
    "epoch = 1000\n",
    "trainer = training.Trainer(updater, (epoch, 'epoch'), out='result')\n",
    "\n",
    "# 評価データで評価\n",
    "trainer.extend(extensions.Evaluator(test_iter, model))\n",
    "\n",
    "# 学習結果の途中を表示する\n",
    "trainer.extend(extensions.LogReport(trigger=(1, 'epoch')))\n",
    "\n",
    "# １エポックごとに、trainデータに対するaccuracyと、testデータに対するaccuracyを出力させる\n",
    "trainer.extend(extensions.PrintReport(['epoch', 'main/accuracy', 'validation/main/accuracy', 'elapsed_time']), trigger=(1, 'epoch'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch       main/accuracy  validation/main/accuracy  elapsed_time\n",
      "\u001b[J1           0.05           0.0809524                 0.0409992     \n",
      "\u001b[J2           0.1            0.0809524                 0.0752184     \n",
      "\u001b[J3           0.116667       0.0809524                 0.108641      \n",
      "\u001b[J4           0.0916667      0.0976191                 0.142788      \n",
      "\u001b[J5           0.0666667      0.0976191                 0.182695      \n",
      "\u001b[J6           0.0571429      0.121429                  0.218414      \n",
      "\u001b[J7           0.0583333      0.138095                  0.255231      \n",
      "\u001b[J8           0.075          0.311905                  0.28676       \n",
      "\u001b[J9           0.308333       0.328571                  0.318105      \n",
      "\u001b[J10          0.241667       0.211905                  0.34918       \n",
      "\u001b[J11          0.271429       0.264286                  0.383913      \n",
      "\u001b[J12          0.341667       0.321429                  0.420599      \n",
      "\u001b[J13          0.366667       0.354762                  0.451992      \n",
      "\u001b[J14          0.458333       0.435714                  0.488302      \n",
      "\u001b[J15          0.5            0.519048                  0.527013      \n",
      "\u001b[J16          0.514286       0.542857                  0.564909      \n",
      "\u001b[J17          0.608333       0.509524                  0.605918      \n",
      "\u001b[J18          0.583333       0.485714                  0.641551      \n",
      "\u001b[J19          0.575          0.52619                   0.669025      \n",
      "\u001b[J20          0.6            0.542857                  0.696596      \n",
      "\u001b[J21          0.585714       0.519048                  0.72542       \n",
      "\u001b[J22          0.533333       0.535714                  0.752053      \n",
      "\u001b[J23          0.558333       0.535714                  0.777505      \n",
      "\u001b[J24          0.566667       0.535714                  0.80253       \n",
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      "\u001b[J38          0.658333       0.585714                  1.12534       \n",
      "\u001b[J39          0.675          0.569048                  1.16518       \n",
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      "\u001b[J42          0.675          0.569048                  1.28828       \n",
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      "\u001b[J44          0.658333       0.569048                  1.37341       \n",
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      "\u001b[J47          0.666667       0.585714                  1.52373       \n",
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      "\u001b[J50          0.7            0.602381                  1.63795       \n",
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      "\u001b[J54          0.675          0.585714                  1.81784       \n",
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      "\u001b[J57          0.733333       0.65                      1.94276       \n",
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      "\u001b[J68          0.825          0.62619                   2.33751       \n",
      "\u001b[J69          0.75           0.65                      2.3652        \n",
      "\u001b[J70          0.716667       0.602381                  2.39352       \n",
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      "\u001b[J72          0.825          0.7                       2.4569        \n",
      "\u001b[J73          0.85           0.72381                   2.48688       \n",
      "\u001b[J74          0.833333       0.65                      2.51614       \n",
      "\u001b[J75          0.775          0.62619                   2.57047       \n",
      "\u001b[J76          0.764286       0.65                      2.60202       \n",
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      "\u001b[J79          0.825          0.707143                  2.68844       \n",
      "\u001b[J80          0.783333       0.65                      2.71242       \n",
      "\u001b[J81          0.771429       0.707143                  2.73939       \n",
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      "\u001b[J83          0.833333       0.666667                  2.78789       \n",
      "\u001b[J84          0.775          0.62619                   2.81023       \n",
      "\u001b[J85          0.75           0.659524                  2.83326       \n",
      "\u001b[J86          0.85           0.747619                  2.86155       \n",
      "\u001b[J87          0.825          0.62619                   2.8831        \n",
      "\u001b[J88          0.741667       0.7                       2.91867       \n",
      "\u001b[J89          0.833333       0.747619                  2.95743       \n",
      "\u001b[J90          0.833333       0.747619                  2.99778       \n",
      "\u001b[J91          0.807143       0.642857                  3.03123       \n",
      "\u001b[J92          0.825          0.747619                  3.05845       \n",
      "\u001b[J93          0.833333       0.642857                  3.08564       \n",
      "\u001b[J94          0.825          0.747619                  3.10968       \n",
      "\u001b[J95          0.816667       0.666667                  3.1377        \n",
      "\u001b[J96          0.771429       0.666667                  3.16143       \n",
      "\u001b[J97          0.85           0.788095                  3.19487       \n",
      "\u001b[J98          0.85           0.747619                  3.232         \n",
      "\u001b[J99          0.783333       0.62619                   3.27131       \n",
      "\u001b[J100         0.808333       0.747619                  3.31381       \n",
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      "\u001b[J102         0.833333       0.666667                  3.39886       \n",
      "\u001b[J103         0.775          0.72381                   3.4391        \n",
      "\u001b[J104         0.858333       0.804762                  3.48011       \n",
      "\u001b[J105         0.866667       0.666667                  3.52382       \n",
      "\u001b[J106         0.807143       0.72381                   3.57125       \n",
      "\u001b[J107         0.85           0.747619                  3.61403       \n",
      "\u001b[J108         0.833333       0.72381                   3.6535        \n",
      "\u001b[J109         0.783333       0.747619                  3.68729       \n",
      "\u001b[J110         0.875          0.771429                  3.72127       \n",
      "\u001b[J111         0.871429       0.747619                  3.76177       \n",
      "\u001b[J112         0.816667       0.707143                  3.79614       \n",
      "\u001b[J113         0.816667       0.747619                  3.83096       \n",
      "\u001b[J114         0.866667       0.747619                  3.86613       \n",
      "\u001b[J115         0.841667       0.72381                   3.90044       \n",
      "\u001b[J116         0.814286       0.72381                   3.93828       \n"
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      "\u001b[J209         0.875          0.861905                  7.93459       \n",
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      "\u001b[J216         0.9            0.878571                  8.20595       \n",
      "\u001b[J217         0.883333       0.878571                  8.23565       \n",
      "\u001b[J218         0.908333       0.861905                  8.27399       \n",
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      "\u001b[J220         0.883333       0.878571                  8.33355       \n",
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      "\u001b[J225         0.875          0.878571                  8.49115       \n",
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      "\u001b[J228         0.908333       0.878571                  8.5841        \n",
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      "\u001b[J234         0.891667       0.878571                  8.75204       \n",
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      "\u001b[J237         0.908333       0.911905                  8.82787       \n",
      "\u001b[J238         0.891667       0.861905                  8.85214       \n"
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      "\u001b[J239         0.891667       0.878571                  8.89301       \n",
      "\u001b[J240         0.908333       0.878571                  8.94194       \n",
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      "\u001b[J289         0.925          0.895238                  10.9595       \n",
      "\u001b[J290         0.908333       0.895238                  10.9866       \n",
      "\u001b[J291         0.914286       0.935714                  11.0156       \n",
      "\u001b[J292         0.908333       0.878571                  11.0421       \n",
      "\u001b[J293         0.9            0.895238                  11.0695       \n",
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      "\u001b[J297         0.908333       0.878571                  11.1856       \n",
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      "\u001b[J299         0.908333       0.895238                  11.2857       \n",
      "\u001b[J300         0.908333       0.878571                  11.353        \n",
      "\u001b[J301         0.914286       0.935714                  11.4063       \n",
      "\u001b[J302         0.908333       0.878571                  11.4578       \n",
      "\u001b[J303         0.9            0.919048                  11.4988       \n",
      "\u001b[J304         0.9            0.935714                  11.5269       \n",
      "\u001b[J305         0.925          0.845238                  11.5538       \n",
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      "\u001b[J309         0.908333       0.935714                  11.6692       \n",
      "\u001b[J310         0.908333       0.878571                  11.7066       \n",
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      "\u001b[J313         0.916667       0.935714                  11.8592       \n",
      "\u001b[J314         0.908333       0.935714                  11.9105       \n",
      "\u001b[J315         0.9            0.878571                  11.9623       \n",
      "\u001b[J316         0.921429       0.895238                  12.0044       \n",
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      "\u001b[J318         0.916667       0.935714                  12.0605       \n",
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      "\u001b[J335         0.908333       0.895238                  12.7437       \n",
      "\u001b[J336         0.921429       0.935714                  12.7875       \n",
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      "\u001b[J338         0.925          0.919048                  12.8665       \n",
      "\u001b[J339         0.925          0.895238                  12.9111       \n",
      "\u001b[J340         0.9            0.935714                  12.9478       \n",
      "\u001b[J341         0.914286       0.895238                  12.992        \n",
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      "\u001b[J350         0.925          0.895238                  13.3445       \n",
      "\u001b[J351         0.892857       0.935714                  13.3743       \n",
      "\u001b[J352         0.95           0.895238                  13.4033       \n",
      "\u001b[J353         0.925          0.919048                  13.4314       \n",
      "\u001b[J354         0.908333       0.895238                  13.4594       \n",
      "\u001b[J355         0.925          0.919048                  13.4875       \n",
      "\u001b[J356         0.907143       0.935714                  13.5182       \n",
      "\u001b[J357         0.925          0.895238                  13.5519       \n",
      "\u001b[J358         0.925          0.935714                  13.5805       \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[J359         0.916667       0.935714                  13.6081       \n",
      "\u001b[J360         0.916667       0.895238                  13.6369       \n",
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      "\u001b[J373         0.916667       0.919048                  14.0256       \n",
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      "\u001b[J472         0.966667       0.935714                  19.0312       \n",
      "\u001b[J473         0.916667       0.935714                  19.0634       \n",
      "\u001b[J474         0.925          0.919048                  19.0969       \n"
     ]
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     "name": "stdout",
     "output_type": "stream",
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      "\u001b[J475         0.941667       0.919048                  19.1313       \n",
      "\u001b[J476         0.928571       0.935714                  19.1881       \n",
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      "\u001b[J555         0.933333       0.878571                  23.6238       \n",
      "\u001b[J556         0.935714       0.919048                  23.7009       \n",
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      "\u001b[J574         0.958333       0.919048                  24.8838       \n",
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      "\u001b[J590         0.941667       0.919048                  25.8388       \n",
      "\u001b[J591         0.942857       0.919048                  25.9114       \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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      "\u001b[J592         0.958333       0.919048                  25.9795       \n",
      "\u001b[J593         0.933333       0.919048                  26.049        \n",
      "\u001b[J594         0.958333       0.919048                  26.1155       \n",
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      "\u001b[J709         0.95           0.902381                  33.8967       \n"
     ]
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      "\u001b[J710         0.966667       0.919048                  33.9749       \n",
      "\u001b[J711         0.957143       0.919048                  34.0613       \n",
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      "\u001b[J820         0.983333       0.92619                   40.7437       \n",
      "\u001b[J821         0.971429       0.92619                   40.8028       \n",
      "\u001b[J822         0.966667       0.92619                   40.8664       \n",
      "\u001b[J823         0.975          0.92619                   40.9331       \n",
      "\u001b[J824         0.975          0.92619                   40.9972       \n",
      "\u001b[J825         0.966667       0.92619                   41.0624       \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[J826         0.971429       0.92619                   41.1336       \n",
      "\u001b[J827         0.975          0.92619                   41.207        \n",
      "\u001b[J828         0.975          0.885714                  41.2975       \n",
      "\u001b[J829         0.975          0.942857                  41.3959       \n",
      "\u001b[J830         0.975          0.92619                   41.4895       \n",
      "\u001b[J831         0.964286       0.92619                   41.5844       \n",
      "\u001b[J832         0.975          0.942857                  41.6687       \n",
      "\u001b[J833         0.975          0.942857                  41.7353       \n",
      "\u001b[J834         0.975          0.942857                  41.8015       \n",
      "\u001b[J835         0.975          0.942857                  41.8698       \n",
      "\u001b[J836         0.964286       0.942857                  41.9413       \n",
      "\u001b[J837         0.966667       0.92619                   42.0085       \n",
      "\u001b[J838         0.975          0.942857                  42.0769       \n",
      "\u001b[J839         0.975          0.92619                   42.1647       \n",
      "\u001b[J840         0.966667       0.92619                   42.2724       \n",
      "\u001b[J841         0.985714       0.909524                  42.3767       \n",
      "\u001b[J842         0.975          0.942857                  42.489        \n",
      "\u001b[J843         0.966667       0.92619                   42.5775       \n",
      "\u001b[J844         0.975          0.942857                  42.6573       \n",
      "\u001b[J845         0.975          0.92619                   42.718        \n",
      "\u001b[J846         0.985714       0.885714                  42.7841       \n",
      "\u001b[J847         0.966667       0.942857                  42.8766       \n",
      "\u001b[J848         0.966667       0.92619                   42.9672       \n",
      "\u001b[J849         0.983333       0.909524                  43.0671       \n",
      "\u001b[J850         0.966667       0.942857                  43.1608       \n",
      "\u001b[J851         0.971429       0.92619                   43.2577       \n",
      "\u001b[J852         0.966667       0.92619                   43.3469       \n",
      "\u001b[J853         0.975          0.885714                  43.4331       \n",
      "\u001b[J854         0.983333       0.92619                   43.5238       \n",
      "\u001b[J855         0.966667       0.92619                   43.6114       \n",
      "\u001b[J856         0.978571       0.909524                  43.6843       \n",
      "\u001b[J857         0.983333       0.92619                   43.7433       \n",
      "\u001b[J858         0.975          0.942857                  43.8171       \n",
      "\u001b[J859         0.975          0.909524                  43.904        \n",
      "\u001b[J860         0.983333       0.909524                  43.9962       \n",
      "\u001b[J861         0.971429       0.92619                   44.0905       \n",
      "\u001b[J862         0.966667       0.92619                   44.1782       \n",
      "\u001b[J863         0.983333       0.942857                  44.2692       \n",
      "\u001b[J864         0.966667       0.92619                   44.3695       \n",
      "\u001b[J865         0.966667       0.92619                   44.4616       \n",
      "\u001b[J866         0.971429       0.909524                  44.5607       \n",
      "\u001b[J867         0.983333       0.92619                   44.6505       \n",
      "\u001b[J868         0.975          0.92619                   44.7178       \n",
      "\u001b[J869         0.975          0.92619                   44.7823       \n",
      "\u001b[J870         0.975          0.909524                  44.8468       \n",
      "\u001b[J871         0.978571       0.942857                  44.9118       \n",
      "\u001b[J872         0.975          0.92619                   44.9736       \n",
      "\u001b[J873         0.983333       0.909524                  45.0379       \n",
      "\u001b[J874         0.983333       0.92619                   45.1013       \n",
      "\u001b[J875         0.975          0.942857                  45.1611       \n",
      "\u001b[J876         0.978571       0.909524                  45.2111       \n",
      "\u001b[J877         0.975          0.92619                   45.2591       \n",
      "\u001b[J878         0.975          0.92619                   45.3116       \n",
      "\u001b[J879         0.966667       0.909524                  45.3591       \n",
      "\u001b[J880         0.983333       0.942857                  45.4072       \n",
      "\u001b[J881         0.971429       0.92619                   45.4571       \n",
      "\u001b[J882         0.983333       0.909524                  45.5071       \n",
      "\u001b[J883         0.983333       0.92619                   45.5609       \n",
      "\u001b[J884         0.975          0.92619                   45.609        \n",
      "\u001b[J885         0.975          0.92619                   45.6616       \n",
      "\u001b[J886         0.978571       0.909524                  45.7094       \n",
      "\u001b[J887         0.983333       0.942857                  45.7578       \n",
      "\u001b[J888         0.966667       0.92619                   45.8042       \n",
      "\u001b[J889         0.966667       0.909524                  45.8506       \n",
      "\u001b[J890         0.975          0.942857                  45.8965       \n",
      "\u001b[J891         0.978571       0.909524                  45.945        \n",
      "\u001b[J892         0.983333       0.92619                   45.9946       \n",
      "\u001b[J893         0.975          0.92619                   46.0451       \n",
      "\u001b[J894         0.983333       0.92619                   46.0944       \n",
      "\u001b[J895         0.983333       0.92619                   46.1426       \n",
      "\u001b[J896         0.978571       0.909524                  46.1947       \n",
      "\u001b[J897         0.975          0.92619                   46.2447       \n",
      "\u001b[J898         0.983333       0.909524                  46.3089       \n",
      "\u001b[J899         0.975          0.909524                  46.4035       \n",
      "\u001b[J900         0.966667       0.92619                   46.5424       \n",
      "\u001b[J901         0.964286       0.909524                  46.6393       \n",
      "\u001b[J902         0.983333       0.92619                   46.7107       \n",
      "\u001b[J903         0.975          0.92619                   46.7779       \n",
      "\u001b[J904         0.966667       0.92619                   46.8446       \n",
      "\u001b[J905         0.983333       0.92619                   46.9098       \n",
      "\u001b[J906         0.978571       0.909524                  46.9802       \n",
      "\u001b[J907         0.983333       0.92619                   47.0523       \n",
      "\u001b[J908         0.958333       0.92619                   47.1174       \n",
      "\u001b[J909         0.958333       0.92619                   47.1729       \n",
      "\u001b[J910         0.975          0.869048                  47.2213       \n",
      "\u001b[J911         0.985714       0.92619                   47.2753       \n",
      "\u001b[J912         0.966667       0.909524                  47.3249       \n",
      "\u001b[J913         0.958333       0.92619                   47.3742       \n",
      "\u001b[J914         0.975          0.92619                   47.4241       \n",
      "\u001b[J915         0.966667       0.909524                  47.4751       \n",
      "\u001b[J916         0.985714       0.92619                   47.5294       \n",
      "\u001b[J917         0.958333       0.942857                  47.579        \n",
      "\u001b[J918         0.975          0.885714                  47.629        \n",
      "\u001b[J919         0.983333       0.92619                   47.6819       \n",
      "\u001b[J920         0.975          0.942857                  47.746        \n",
      "\u001b[J921         0.978571       0.92619                   47.8458       \n",
      "\u001b[J922         0.983333       0.942857                  47.945        \n",
      "\u001b[J923         0.975          0.909524                  48.0425       \n",
      "\u001b[J924         0.966667       0.909524                  48.1326       \n",
      "\u001b[J925         0.983333       0.942857                  48.203        \n",
      "\u001b[J926         0.971429       0.92619                   48.2804       \n",
      "\u001b[J927         0.991667       0.909524                  48.3597       \n",
      "\u001b[J928         0.983333       0.942857                  48.4859       \n",
      "\u001b[J929         0.975          0.92619                   48.5777       \n",
      "\u001b[J930         0.975          0.909524                  48.6677       \n",
      "\u001b[J931         0.964286       0.942857                  48.7465       \n",
      "\u001b[J932         0.983333       0.909524                  48.8264       \n",
      "\u001b[J933         0.983333       0.909524                  48.9022       \n",
      "\u001b[J934         0.983333       0.942857                  48.9811       \n",
      "\u001b[J935         0.975          0.942857                  49.0586       \n",
      "\u001b[J936         0.992857       0.845238                  49.1113       \n",
      "\u001b[J937         0.966667       0.942857                  49.1628       \n",
      "\u001b[J938         0.975          0.942857                  49.2123       \n",
      "\u001b[J939         0.983333       0.909524                  49.2622       \n",
      "\u001b[J940         0.975          0.909524                  49.3165       \n",
      "\u001b[J941         0.985714       0.942857                  49.3738       \n",
      "\u001b[J942         0.983333       0.909524                  49.4281       \n",
      "\u001b[J943         0.983333       0.909524                  49.4813       \n",
      "\u001b[J944         0.983333       0.909524                  49.536        \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[J945         0.983333       0.92619                   49.5887       \n",
      "\u001b[J946         0.971429       0.92619                   49.6565       \n",
      "\u001b[J947         0.991667       0.942857                  49.731        \n",
      "\u001b[J948         0.983333       0.909524                  49.815        \n",
      "\u001b[J949         0.983333       0.909524                  49.9106       \n",
      "\u001b[J950         0.983333       0.942857                  50.0078       \n",
      "\u001b[J951         0.978571       0.92619                   50.1251       \n",
      "\u001b[J952         0.975          0.909524                  50.2059       \n",
      "\u001b[J953         0.983333       0.942857                  50.2832       \n",
      "\u001b[J954         0.975          0.92619                   50.3624       \n",
      "\u001b[J955         0.983333       0.92619                   50.4431       \n",
      "\u001b[J956         0.978571       0.909524                  50.5237       \n",
      "\u001b[J957         0.991667       0.909524                  50.6003       \n",
      "\u001b[J958         0.983333       0.942857                  50.7017       \n",
      "\u001b[J959         0.975          0.909524                  50.7986       \n",
      "\u001b[J960         0.983333       0.909524                  50.8962       \n",
      "\u001b[J961         0.985714       0.942857                  50.9948       \n",
      "\u001b[J962         0.966667       0.942857                  51.0923       \n",
      "\u001b[J963         0.983333       0.909524                  51.1975       \n",
      "\u001b[J964         0.975          0.92619                   51.305        \n",
      "\u001b[J965         0.983333       0.942857                  51.411        \n",
      "\u001b[J966         0.992857       0.92619                   51.5653       \n",
      "\u001b[J967         0.983333       0.909524                  51.6789       \n",
      "\u001b[J968         0.983333       0.92619                   51.777        \n",
      "\u001b[J969         0.983333       0.909524                  51.883        \n",
      "\u001b[J970         0.975          0.942857                  51.988        \n",
      "\u001b[J971         0.985714       0.909524                  52.0912       \n",
      "\u001b[J972         0.975          0.942857                  52.2101       \n",
      "\u001b[J973         0.991667       0.92619                   52.2745       \n",
      "\u001b[J974         0.983333       0.92619                   52.3399       \n",
      "\u001b[J975         0.983333       0.909524                  52.4069       \n",
      "\u001b[J976         0.985714       0.92619                   52.4739       \n",
      "\u001b[J977         0.975          0.92619                   52.5405       \n",
      "\u001b[J978         0.983333       0.92619                   52.609        \n",
      "\u001b[J979         0.983333       0.92619                   52.6707       \n",
      "\u001b[J980         0.983333       0.909524                  52.7231       \n",
      "\u001b[J981         0.985714       0.92619                   52.7777       \n",
      "\u001b[J982         0.983333       0.909524                  52.8284       \n",
      "\u001b[J983         0.983333       0.909524                  52.8787       \n",
      "\u001b[J984         0.983333       0.909524                  52.9296       \n",
      "\u001b[J985         0.983333       0.92619                   52.981        \n",
      "\u001b[J986         0.992857       0.942857                  53.0346       \n",
      "\u001b[J987         0.975          0.909524                  53.0863       \n",
      "\u001b[J988         0.991667       0.909524                  53.1365       \n",
      "\u001b[J989         0.991667       0.942857                  53.201        \n",
      "\u001b[J990         0.983333       0.909524                  53.3          \n",
      "\u001b[J991         0.985714       0.92619                   53.4025       \n",
      "\u001b[J992         0.983333       0.909524                  53.4965       \n",
      "\u001b[J993         0.983333       0.909524                  53.5955       \n",
      "\u001b[J994         0.983333       0.942857                  53.6819       \n",
      "\u001b[J995         0.991667       0.909524                  53.7537       \n",
      "\u001b[J996         0.985714       0.92619                   53.8288       \n",
      "\u001b[J997         0.983333       0.909524                  53.9113       \n",
      "\u001b[J998         0.983333       0.92619                   53.9835       \n",
      "\u001b[J999         0.991667       0.92619                   54.0563       \n",
      "\u001b[J1000        0.983333       0.909524                  54.1373       \n"
     ]
    }
   ],
   "source": [
    "# 学習実行してくだされ～\n",
    "trainer.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 学習結果確認しますかー"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "with open('result/log') as f:\n",
    "     logs = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "result_train = [ log['main/loss'] for log in logs ]\n",
    "result_test  = [ log['validation/main/loss'] for log in logs ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BPcA3zew3ZnaPmTVUqa6yipYk0AxdRKSsuQR6Ergc+Jq7XwYMAndMvpOZbTCzLjPr6unp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\nRijQRURqhAJdRKRGKNBFRGrE/wdi7IYCWj6RqQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e449bfe10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.plot(result_train, label='train')  # 訓練データ\n",
    "plt.plot(result_accuracy, label='accuracy')  # accuracy\n",
    "plt.plot(result_test,  label='test')  # 検証データ\n",
    "plt.legend()  # 凡例表示\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Accuracy も見ておこう、上司とかに報告する際はこっちになりますしお寿司"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "result_accuracy = [ log['main/accuracy'] for log in logs ]\n",
    "result_accuracy_test  = [ log['validation/main/accuracy'] for log in logs ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vaq1r2SsnvMz/f8PYU3iKUd1bBXZCvXT3d7a1DdtZUoUQZ0AgOfeBQJ7Weqcj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\niEAS3IUQIgL9fxHmsTuBa2iGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5e4486c240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.plot(result_accuracy, label='accuracy')  # 訓練データ\n",
    "plt.plot(result_accuracy_test,  label='test')  # 検証データ\n",
    "plt.legend()  # 凡例表示\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}