stack_mlp_level2.py 文件源码

def MLP(opt='nadam'):

    X_raw=Input(shape=(LEN_RAW_INPUT,),name='input_raw')

    fc1=BatchNormalization()(X_raw)
    fc1=Dense(256)(fc1)
    fc1=PReLU()(fc1)
    fc1=Dropout(0.2)(fc1)

    fc1=BatchNormalization()(fc1)
    fc1=Dense(256)(fc1)
    fc1=PReLU()(fc1)
    #fc1=Dropout(0.2)(fc1)

    fc1=BatchNormalization()(fc1)
    auxiliary_output_dense = Dense(1, activation='sigmoid', name='aux_output_dense')(fc1)


    output_all = Dense(1,activation='sigmoid',name='output')(fc1)
    model=Model(input=X_raw,output=output_all)
    model.compile(
                optimizer=opt,
                loss = 'binary_crossentropy')
    return model


#nadam=Nadam(lr=0.000)