solving multi-class imbalance classification using smote and OSS I am trying to solve multi-class imbalance classification problem for that i am using SMOTE for oversampling and OSS for under-sampling. But I have a doubt as I am working on multi-class so i have to convert it into binary classification. So we can convert it using OVA/OAA. So how can I use OVA/OAA with both under-sampling and oversampling on the same data-set.

Please solve my problem, It will be a great help.
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