FairCORELS, an Open-Source Library for Learning Fair Rule Lists

FairCORELS is an open-source Python module for building fair rule lists. It is a multi-objective variant of CORELS, a branch-and-bound algorithm to learn certifiably optimal rule lists. FairCORELS supports six statistical fairness metrics, proposes several exploration parameters and leverages on the fairness constraints to prune the search space efficiently. It can easily generate sets of accuracy-fairness trade-offs. The models learnt are interpretable by design and a sparsity parameter can be used to control their length.

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