My dataset has the following class distribution
CLASS FREQUENCY 2 22696 4 2541 1 2093 5 1298 3 1116 0 960 6 14
definitely I would want to generate a new sample, for that I will use python imblearn , I have three options:
- oversample the minority classes
- undersample the majority classes
- choose a median class and apply both undersample the majority classes and oversamples the minority classes to equal the median class.
Later I will use the generated dataset to train three estimators RandomForest classifier, SVC and ensemble of both. I will choose the one with the best f-1 score. what would be the best option and which oversampling/undersampling algo should I use?