train_predict_krs1.py 文件源码

def nn_model(dims):
    model = Sequential()

    model.add(Dense(400, input_dim=dims, 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(1, init='he_normal'))
    model.compile(loss = 'mae', optimizer = 'adadelta')
    return(model)