I'm trying to apply xgboost and random forest for over and under sampling
for imbalance data

train shape -> (199991, 23)

but reverse my expectation.
the accuracy is went down for both case

1. is under and over sampling always not good?
   

2. what else do I have to consider when I apply over and under sampling?
   

3. xgboost randomforest

4. under over sampling

5. multi calssification

6. imbalanced dataset

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.

Questions:

1. Is under and over sampling always not good?
2. What else should I consider when applying over and under sampling?