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Port micellaneous items to sklearn-compatible API #150
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@hoffmansc Do you skeleton for this conversion? |
I don't really have skeletons for these but I thought examples would be enough: For the MEPS dataset, a good place to start might be the COMPAS port. For differential fairness, you could look at any number of the already ported metrics. |
@hoffmansc I will take a look at it this week. |
New to contributing. Can I take a crack at this? @hoffmansc |
we'd love it if you did |
Great. I'll give it a go. |
Sorry! I got this confused with another issue. I have some work in progress for the first two but rich subgroup fairness is still outstanding. @mkrueger12 |
Sounds good. I can work on rich subgroup fairness. @hoffmansc |
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