This repository provides a python implementation of our AAAI'18 paper titled ''Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning''.

numpy, scipy, pandas and sklearn

If you want to use the code related to [1], please navigate to the directory "fair_feature_selection".

Please cite this paper when using the code.

1. Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning
   by Nina Grgić-Hla&#269a, Muhammad Bilal Zafar, Krishna P. Gummadi, and Adrian Weller
   To Appear in the Proceedings of the 32nd AAAI Conference on Artificial Inteligence (AAAI), New Orleans, Louisiana, February 2018.