English Translation:
When applying a three-dimensional dataset for LSTM training, an error is reported: Invalid training data. The predictor and response must have the same number of observations. I applied the sliding window technique to convert the original time series’ two-dimensional XTrain and YTrain into a three-dimensional cell array. In this, the numsamples-windowsize of the corresponding sequence in XTrain and YTrain has been checked and is equal, and its value corresponds to the number of time steps. The above XTrain and YTrain are input into the following LSTM network.
However, during training, an error occurred, the content is: Invalid training data. The predictor and response must have the same number of observations.
What is the cause of this? If anyone can provide any help, I would be very grateful.
