model = Sequential()
model.add(LSTM(12, input_shape=(1, window)))
model.add(Dense(1))
model.compile(loss='mean_squared_error', optimizer='adam')
history = model.fit(train_X, train_y, epochs=20, batch_size=1, verbose=2,
        validation_data=(validate_X, validate_y))
return(model, history)