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In your model code, I find you used data scaler for train\val\test dataset separately. However, I think you probably use future information during validating and testing process. Because, during the online prediction, we can't get the whole data in advance. In addition, I didn't find inverse transformation, which is important to show the real model performance for testing dataset. Can you give more information as to how to deal with data scaling and inverse transformation? Thanks.
The text was updated successfully, but these errors were encountered:
Thank you very much for your reminder, train data should be used to calculate mean and std when scaling data, while validation data and test data should only be scaled.
We will fix the above problems and the inverse_transform problem immediately.
Thank you very much for your reminder, train data should be used to calculate mean and std when scaling data, while validation data and test data should only be scaled.
We will fix the above problems and the inverse_transform problem immediately.
Thanks!
Thanks, could you remind me an update if it is done?
In your model code, I find you used data scaler for train\val\test dataset separately. However, I think you probably use future information during validating and testing process. Because, during the online prediction, we can't get the whole data in advance. In addition, I didn't find inverse transformation, which is important to show the real model performance for testing dataset. Can you give more information as to how to deal with data scaling and inverse transformation? Thanks.
The text was updated successfully, but these errors were encountered: