Hello everyone, I am running an undersampling algorithm from imblearn, and at the back I want to train several gbms (catboost, xgb, lgbm, etc) with successivehalving to optimize the hyperparams. Based on imblearn docs, I need to set up the undersampler within a pipeline, but that's innefficient, because in theory, I could undersample all 3 folds of the training data, store the left out folds with the original distribution, and then on those, train the various models with SH. So my question is: how can I pass data folds (undersampled for training and original for the left out) to successive halving (or any hyperparam search for that matter)? I posted a [question on stackoverflow](https://stackoverflow.com/questions/79748461/how-to-pass-pre-computed-folds-...) with this issue. Sharing it here in case someone knows. Thanks a lot! Best Sole Soledad Galli https://www.trainindata.com/