Keras时间序列输出密集多个不起作用

Question

我想一次预测6个月的时间序列。我设置了model.add（Dense（6）），但是它显示了这样的错误。

  

ValueError：检查输入时出错：预期density_1_input具有   形状（6，），但数组的形状为（1，）

这是我的代码。

df = pd.read_csv('D://data.csv',
                 engine='python')

    df['DATE_'] = pd.to_datetime(df['DATE_']) + MonthEnd(1)
    df = df.set_index('DATE_')
    df.head()


    split_date = pd.Timestamp('03-01-2015')

    train = df.loc[:split_date, ['data']]
    test = df.loc[split_date:, ['data']]

    sc = MinMaxScaler()

    train_sc = sc.fit_transform(train)
    test_sc = sc.transform(test)

    X_train = train_sc[:-1]
    y_train = train_sc[1:6]


    X_test = test_sc[:-1]
    y_test = test_sc[1:6]

    K.clear_session()
    model = Sequential()
    model.add(Dense(12, input_dim=6, activation='relu'))
    model.add(Dense(6))
    model.compile(loss='mean_squared_error', optimizer='adam')
    model.summary()

    model.fit(X_train, y_train, epochs=200, batch_size=2)

    y_pred = model.predict(X_test)

    real_pred = sc.inverse_transform(y_pred)
    real_test = sc.inverse_transform(y_test)

    print("Predict Value")
    print(real_pred)

    print("Test Value")
    print(real_test)