質問編集履歴
2
予測用のコードを追加
test
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File without changes
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test
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@@ -133,3 +133,45 @@
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```
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予測用のコード
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140
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141
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```python
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142
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143
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from keras.models import load_model
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import numpy as np
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import csv
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148
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test_data=[]
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152
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with open('test.csv') as f:
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reader = csv.reader(f)
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for row in reader:
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test_data.append(row)
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162
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test_data1 = np.array(test_data,dtype=np.float64)
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166
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167
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168
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169
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model = load_model("model.h5")
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result = model.predict_classes(test_data1)
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174
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175
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print(result)
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176
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177
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```
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1
修正後のソースコードを追加しました
test
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File without changes
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test
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@@ -79,3 +79,57 @@
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79
79
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model.fit(train_data1,train_label1, epochs=300, validation_split=0.1)
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80
80
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```
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82
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84
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85
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修正後のソースコード
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86
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87
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```python
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88
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89
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# Sequentialモデル使用(Sequentialモデルはレイヤを順に重ねたモデル)
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90
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91
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model = Sequential()
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92
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93
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94
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95
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model.add(Dense(1900, activation='relu', input_shape = ( 950, )))
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96
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97
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model.add(Dropout(0.5))
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98
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99
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100
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101
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model.add(Dense(500, activation='relu'))
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103
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model.add(Dropout(0.5))
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104
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105
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106
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model.add(Dense(1, activation='linear'))
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108
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109
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110
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111
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# モデルをコンパイル
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112
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113
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model.compile(loss="mean_squared_error", optimizer="sgd", metrics=["accuracy"])
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114
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115
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116
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117
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model.summary()
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118
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119
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120
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121
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#訓練
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122
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123
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model.fit(train_data1,train_label1, epochs=300, validation_split=0.1)
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124
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125
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model.save('model.h5')
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126
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127
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128
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129
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score = model.evaluate(test_data1, test_result1)
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130
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131
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print("正解率: %.2f%%" % (score[1] * 100))
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133
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134
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```
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