Aequitas is a directed fairness testing framework machine learning models. See the paper Automated Directed Fairness Testing for more details.
There are 3 test generation strategies in our suite, namely Aequitas Random, Aequitas Semi-Directed and Aequitas Fully Directed. There are files to evaluate Fair SVM and Scikit-Learn classifiers trained on the same dataset.
- Aequitas now supports non-binary, multi-dimensional sensitive feature.
- Aequitas now supports multiple sensitive features to be in the same data set.
Phemus is a software tool aimed to provide fairness assessment and improvement for machine learning datasets.
Aequitas Web is a web interface to Aequitas.
Please visit our archive website to learn more about our project.
This work is based on the technology developed in the following conference proceeding:
title: Automated directed fairness testing}
author: Udeshi, Sakshi and Arora, Pryanshu and Chattopadhyay, Sudipta
booktitle: Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering
pages: 98--108
year: 2018
Liscened by the original authors