If you convert your problem to a binary classification task, you do not need to worry about any conflict with re-sampling techniques. You can then just use the imblearn.combine which combines Oversampling and under-sampling in one algorithm. There are classes available for this but I have found SMOTEENN to produce better results. SMOTEENN
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