预测中的LSTM错误形状

Question

我训练了一个模特：

trainX = trainX.reshape(1, 43164, 17)
trainY = trainY.reshape(43164, 1)

model = Sequential()
model.add(LSTM(2, input_shape=(43164, 17)))
model.add(Dense(1))
model.compile(loss='mean_squared_error', optimizer='adam')
model.fit(trainX, trainY[0], epochs=100)

testX.shape # (8633, 17)
testX = testX.reshape(1, 8633, 17)

当我对这些数据进行预测时，我得到了一个错误：

Error when checking input: expected lstm_26_input to have shape (43164, 17) 
but got array with shape (8633, 17)

为了得到好的结果我能做些什么

Answer 1

在深度学习网络的Sequential modesls中，你既可以用有限的短窗口传递数据，也可以用改变窗口的步幅传递数据

用一维向量传递所有序列

trainX = trainX.reshape( 43164,1, 17)
trainY = trainY.reshape(43164, 1)

model = Sequential()
model.add(LSTM(2, input_shape=(1, 17)))
model.add(Dense(1))
model.compile(loss='mean_squared_error', optimizer='adam')
model.fit(trainX, trainY[0], epochs=100)

testX.shape # (8633, 17)
testX = testX.reshape(8633,1, 17)