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Awesome @rensoostenbach! In case somebody else starts working on #1027 it would be good to coordinate, but for now it is just additional info.

For whoever will work on this, note @adrinjalali's suggestion in [this comment](https://github.com/fairlearn/fairlearn/pull/1109#pullrequestreview-1011501704): > One way to fix the original issue is to automatically have links to all examples from the...

At a first glance it seems like @Dref360 has processed al requested changes from @riedgar-ms. Is there anything else that's blocking this PR from getting merged? Tagging @fairlearn/fairlearn-maintainers

The end of February has passed, are there still things that need to be resolved for this to be merged? @MiroDudik @riedgar-ms @adrinjalali @romanlutz

This PR is now ready for review! Tagging @fairlearn/fairlearn-maintainers

I like that the proposed API suggests that bootstrapping is part of the default workflow of fairness assessments, but I don't have a very strong opinion on this one. I...

For binary/multiclass there's a whole bunch of [utils in scikit-learn](https://github.com/scikit-learn/scikit-learn/blob/844b4be24d20fc42cc13b957374c718956a0db39/sklearn/utils/multiclass.py) that may be of help. For regression a separate `AdversarialMitigationRegressor` class seems more intuitive to me (this is also a...

> Or is there a lot of use for also supporting multiclass features, and letting the users map various groups of columns of sensitive_features? Tutorials like to pretend that everything...

@MiroDudik did you hear back from your colleague regarding ranking metrics?

Tagging @MiroDudik