相关疑难解决方法(0)

我正在尝试将我的GRU模型与我的训练数据相匹配时遇到问题.快速浏览StackOverflow后,我发现这篇文章与我的问题非常相似:

最简单的Lstm培训与Keras io

我自己的模型如下:

nn = Sequential()
nn.add(Embedding(input_size, hidden_size))
nn.add(GRU(hidden_size_2, return_sequences=False))
nn.add(Dropout(0.2))
nn.add(Dense(output_size))
nn.add(Activation('linear'))

nn.compile(loss='mse', optimizer="rmsprop")

history = History()
nn.fit(X_train, y_train, batch_size=30, nb_epoch=200, validation_split=0.1, callbacks=[history])

错误是:

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-14-e2f199af6e0c> in <module>()
      1 history = History()
----> 2 nn.fit(X_train, y_train, batch_size=30, nb_epoch=200, validation_split=0.1, callbacks=[history])

C:\Users\XXXX\AppData\Local\Continuum\Anaconda\lib\site-packages\keras\models.pyc in fit(self, X, y, batch_size, nb_epoch, verbose, callbacks, validation_split, validation_data, shuffle, show_accuracy, class_weight, sample_weight)
    487                          verbose=verbose, callbacks=callbacks,
    488                          val_f=val_f, val_ins=val_ins,
--> 489                          shuffle=shuffle, metrics=metrics)
    490 
    491     def predict(self, X, batch_size=128, verbose=0): …