Re: [scikit-learn] Fairness Metrics

2018-11-01 Thread Feldman, Joshua
Thanks Andy, I'll look into starting a scikit-learn-contrib project! Best, Josh ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Fairness Metrics

2018-10-30 Thread Andreas Mueller
Hi Josh. Yes, as I mentioned briefly in my second email, you could start a scikit-learn-contrib project that implements these. Or, if possible, show how to use Aequitas with sklearn. This would be interesting since it probably requires some changes to the API, as our scorers have no

Re: [scikit-learn] Fairness Metrics

2018-10-30 Thread Feldman, Joshua
Hi Andy, Yes, good point and thank you for your thoughts. The Aequitas project stood out to me more because of their flowchart than their auditing software because, as you mention, you always fail the report if you include all the measures! Just as with choosing a machine learning algorithm,

Re: [scikit-learn] Fairness Metrics

2018-10-30 Thread Andreas Mueller
Would be great for sklearn-contrib, though! On 10/29/18 1:36 AM, Feldman, Joshua wrote: Hi, I was wondering if there's any interest in adding fairness metrics to sklearn. Specifically, I was thinking of implementing the metrics described here: https://dsapp.uchicago.edu/projects/aequitas/

[scikit-learn] Fairness Metrics

2018-10-28 Thread Feldman, Joshua
Hi, I was wondering if there's any interest in adding fairness metrics to sklearn. Specifically, I was thinking of implementing the metrics described here: https://dsapp.uchicago.edu/projects/aequitas/ I recognize that these metrics are extremely simple to calculate, but given that sklearn is