from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
from keras.layers import Dropout
regressor = Sequential()
regressor.add(LSTM(units = 50, return_sequences= True, input_shape = (X_train.shape[0],2)))
regressor.add(Dropout(rate = 0.2))
regressor.add(LSTM(units = 50, return_sequences= True))
regressor.add(Dropout(rate = 0.2))
regressor.add(LSTM(units = 50))
regressor.add(Dropout(rate = 0.2))
regressor.add(Dense(units = 1))
regressor.compile(optimizer= 'adam', loss = 'mean_squared_error', metrics = ['accuracy'])
regressor.fit(X_train, y_train, batch_size = 1000, epochs = 25)'
Я пытаюсь предсказать значение y_train
, основываясь на двух особенностях X_train
. Я получаю сообщение об ошибке: ValueError: Error when checking input: expected lstm_3_input to have 3 dimensions, but got array with shape (10000, 2)