Created
November 18, 2017 07:39
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| from keras.layers import Dense, Dropout, Input, BatchNormalization | |
| from keras.models import Model | |
| def get_nn_model(dropout=0.6): | |
| inp = Input(shape = (90,)) | |
| x = Dense(100, activation='relu')(inp) | |
| x = BatchNormalization()(x) | |
| x = Dropout(dropout)(x) | |
| x = Dense(50, activation='relu')(x) | |
| x = BatchNormalization()(x) | |
| x = Dropout(dropout)(x) | |
| x = Dense(50, activation='relu')(x) | |
| x = BatchNormalization()(x) | |
| x = Dropout(dropout)(x) | |
| x = Dense(1, activation='sigmoid')(x) | |
| model = Model(inputs=[inp], outputs=[x]) | |
| model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy']) | |
| return model |
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