classification.py 文件源码

def create_net():
    model = Sequential()

    model.add(Dense(400, input_dim = X_train.shape[1], init = 'he_normal'))
    model.add(PReLU())
    model.add(BatchNormalization())
    model.add(Dropout(0.4))

    model.add(Dense(200, init = 'he_normal'))
    model.add(PReLU())
    model.add(BatchNormalization())
    model.add(Dropout(0.2))

    model.add(Dense(50, init = 'he_normal'))
    model.add(PReLU())
    model.add(BatchNormalization())
    model.add(Dropout(0.2))

    model.add(Dense(output_dim=10, init = 'he_normal'))
    model.add(Activation('softmax'))
    model.compile(loss='categorical_crossentropy', optimizer='sgd',
                  metrics=['categorical_accuracy'])
    return(model)