I'm trying to apply xgboost and random forest for over and under sampling
For imbalanced data:
train shape -> (199991, 23)
However, reverse my expectation. The accuracy went down for both cases.
- Is under and over sampling always not good?
- What else should I consider when applying over and under sampling?