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Synthetic Minority Oversampling Technique (SMOTE) is an approach used for dealing with imbalanced datasets before running them through machine learning models.
13
votes
Oversampling/Undersampling only train set only or both train and validation set
Oversample the train data and NOT the validation data since if train data is unbalanced, your test data will most likely show the same trait and be unbalanced.
If you don't know if test data will be b …