08 October 2021 0 300 Report

Generally, data augmentation techniques have shown effectiveness for the classification problem.

For example, SMOTE is widely used for imbalanced classification.

How about the regression problem?

Can anyone recommend any effective over-sampling approaches for the regression problem?

I've read some papers about SMOTE for regression and SMOGN.

However, I'm not sure that they can surprisingly increase the prediction performance, yet.

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