[scikit-learn] Fairness Metrics
t3kcit at gmail.com
Tue Oct 30 11:57:40 EDT 2018
I think this would be cool to add at some point, I'm not sure this is now.
I'm a bit surprised by their "fairness report". They have 4 different
metrics of fairness which are conflicting.
If they are all included in the fairness report then you always fail the
fairness report, right?
I think it would also be great to provide a tool to change predictions
to be fair according to one of these
I don't think there is consensus yet that these metrics are "good", in
particular since they are conflicting,
and so people are trying to go beyond these, I think.
On 10/29/18 1:36 AM, Feldman, Joshua wrote:
> I was wondering if there's any interest in adding fairness metrics to
> sklearn. Specifically, I was thinking of implementing the metrics
> described here:
> I recognize that these metrics are extremely simple to calculate, but
> given that sklearn is the standard machine learning package in python,
> I think it would be very powerful to explicitly include algorithmic
> fairness - it would make these methods more accessible and, as a
> matter of principle, demonstrate that ethics is part of ML and not an
> afterthought. I would love to hear the groups' thoughts and if there's
> interest in such a feature.
> scikit-learn mailing list
> scikit-learn at python.org
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