python
1import keras 2from keras.layers import Activation, Dense, Dropout 3from keras.models import Sequential 4from sklearn.preprocessing import MinMaxScaler 5from tensorflow.keras.callbacks import EarlyStopping 6from tensorflow.keras.optimizers import Adam 7import pandas as pd 8import numpy as np 9import matplotlib.pyplot as plt 10 11#学習データ12data = pd.DataFrame(13 [14 #No.115 [9.0, 2701, 1477, 2000, 1475, 0.4018],16 17 #No.218 [8.4,1675,773,2000,1364,0.2888],19 #No.320 [6.6,7777,54,2000,1176,0.1017],21 22 #No.423 [7.3,9686,178,1521,2000,0.1556],24 25 #No.526 [7.1,3089,1840,2000,1188,0.0491],27 28 #No.629 [7.8,9441,205,1322,2000,0.2298],30 31 #No.732 [6.5,4763,1242,1588,2000,0.0790],33 34 #No.835 [8.9,6498,1865,1943,2000,0.3776],36 37 #No.938 [8.0,2489,568,1658,2000,0.2597],39 40 #No.1041 [6.0,7839,823,1310,2000,0.0766],42 43 #No.1144 [9.0,7941,1004,1720,2000,0.4532],45 46 #No.1247 [7.5,1452,698,2000,219,0.1003],48 49 #No.1350 [6.9,6007,1246,2000,257,0.0373],51 52 #No.1453 [8.7,8671,1744,1999,2000,0.3207],54 55 #No.1556 [8.1,86554,951,2000,26,0.1521],57 58 #No.1659 [7.0,81375,985,1400,2000,0.0912],60 61 #No.1762 [8.6,32889,1274,2000,623,0.2294],63 64 #No.1865 [9.0,48790,1446,2000,1987,0.4439],66 67 #No.1968 [7.3,59028,817,832,2000,0.1194],69 70 #No.2071 [7.9,68181,1512,1608,2000,0.1954],72 73 #No.2174 [6.1,93928,401,1395,2000,0.0890],75 76 #No.2277 [6.2,85892,6,81,2000,0.0626],78 79 #No.2380 [7.9,72570,1095,2000,81,0.1240],81 82 #No.2483 [9.0,86521,1392,1488,2000,0.4348],84 85 #No.2586 [6.9,34140,1716,2000,779,0.0370],87 88 #No.2689 [8.7,42481,875,2000,1923,0.4056],90 91 #No.2792 [6.5,12369,1715,1897,2000,0.0730],93 94 #No.2895 [8.7,22112,264,1876,2000,0.4341],96 97 #No.2998 [8.4,15363,58,2000,39,0.2479],99 100 #No.30101 [6.3,15165,195,955,2000,0.0884],102 103 #No.31104 [7.3,68657,1864,1978,2000,0.0797],105 106 #No.32107 [9.0,96352,15,1835,2000,0.4341],108 109 #No.33110 [6.7,735959,331,387,2000,0.0619],111 112 #No.34113 [9.0,531601,555,2000,1733,0.2679],114 115 #No.35116 [7.9,852996,612,2000,589,0.1109],117 118 #No.36119 [8.9,415339,1507,1586,2000,0.2668],120 121 #No.37122 [8.4,499514,1756,1820,2000,0.1504],123 124 #No.38125 [6.4,973579,122,2000,1941,0.0892],126 127 #No.39128 [6.1,436622,1704,2000,1388,0.0436],129 130 #No.40131 [9.0,360412,864,2000,594,0.2271],132 133 #No.41134 [8.5,646469,73,828,2000,0.1500],135 136 #No.42137 [7.2,908067,1790,1820,2000,0.0688],138 139 #No.43140 [7.3,977526,1662,2000,1013,0.0427],141 142 #No.44143 [6.5,130665,904,1112,2000,0.0719],144 145 #No.45146 [9.0,144155,1088,2000,1069,0.3495],147 148 #No.46149 [7.6,229788,150,2000,1730,0.1563],150 151 #No.47152 [7.8,645105,84,2000,870,0.1276],153 154 #No.48155 [6.9,500021,995,1109,2000,0.0735],156 157 #No.49158 [8.5,294460,690,2000,1748,0.2675],159 160 ],161 columns = ['M','t','X1','X2','Y2','uSv/y']162)163df = pd.DataFrame(data)164 165#説明変数166in_data = df.iloc[:, 0:5]167 168#目的変数169out_data = df['uSv/y']170 171#正規化172scaler = MinMaxScaler()173in_data = pd.DataFrame(scaler.fit_transform(in_data))174print(in_data)175 176#ndarrayに変換177in_data=np.array(in_data)178out_data=np.array(out_data)179 180#モデルの生成181model = keras.models.Sequential()182model.add(Dense(units = 64,input_dim=(5)))183model.add(Activation('relu'))184model.add(Dense(units = 64 ))185model.add(Activation('relu'))186model.add(Dense(1))187 188 189#モデルのコンパイル190model.compile(191 loss = 'mse',192 optimizer = 'adam',193 metrics = ['mae'])194 195#Earlystopping196ealy_stop = EarlyStopping(monitor='val_loss',patience=30)197 198#学習199history = model.fit(in_data, out_data, epochs=1000,validation_split=0.2,200 callbacks=[ealy_stop])201 202#テストデータ203test_data = np.array(204 [205 #No.50206 [7.0,5647,1000,1266,2000],207 [6.3,75894,539,1111,2000],208 [8.5,142747,1788,2000,242],209 [6.8,16474,539,1266,1600],210 [9.0,174947,539,1266,2000],211 [7.7,75947,539,1266,2000]212 ]213)214 215#正規化216scaler = MinMaxScaler()217test_data = pd.DataFrame(scaler.fit_transform(test_data))218print(test_data)219 220#予測221result = np.argmax(model.predict(test_data) ,axis=1)222 223#予測結果の出力224print(result)225 226#正解の出力227print(out_data)228
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