Mateusz Garbacz

I will pick up the issue

This PR is ready for review

Hi @lopuhin , sorry for the delay. I have implemented the suggestions from your comment.

I suppose this could be fixed using imbalanced-learn Pipeline or implementing own pipeline that allows this kind of actions. What are your thoughts on it?

I see the point of keeping it, but indeed we need to keep it as simple as possible. I would say if we indeed want to keep it i think...

We use `pre-commit` hook https://github.com/ing-bank/probatus/blob/main/.pre-commit-config.yaml. This file describes all standards. Contributing file mentions that you need to install pre-commit first.

I suppose if you perform such analysis you can find: - Groups in your data that affect the model in a certain way e.g. these samples cause prediction mainly of...

@rchaves33 Will you be picking this one up? Or shall we close it for now? There is another PR that will modify some of the functions you are working on....

@eduardo-lourenco Are you going to still work on this one PR?

I think this would be a great addition, and relatively easy to implement. in line 558 of feature_elimination.py: ``` self._report_current_results( round_number=round_number, current_features_set=current_features_set, features_to_remove=features_to_remove, train_metric_mean=np.round(np.mean(scores_train), 3), train_metric_std=np.round(np.std(scores_train), 3), val_metric_mean=np.round(np.mean(scores_val), 3), val_metric_std=np.round(np.std(scores_val),...