用Python进行LSTM预测算法

def build_model():
    grid_model = Sequential()
    grid_model.add(LSTM(50, return_sequences=True, input_shape=(30,5)))
    grid_model.add(LSTM(56))
    grid_model.add(Dropout(0.2))
    grid_model.add(Dense(1))
    grid_model.compile(loss='mse', optimizer='adam')
    return grid_model

grid_model = KerasRegressor(build_fn=build_model, verbose=1)

parameters = {
    'batch_size': [16, 20],
    'epochs': [8, 10],
    'optimizer': ['adam', 'Adadelta']
}

grid_search = GridSearchCV(estimator=grid_model, param_grid=parameters, cv=2)
grid_search = grid_search.fit(trainX, trainY, validation_data=(testX, testY))