FairBalance: How to Achieve Equalized Odds With Data Pre-processing

Understand

This research seeks to benefit the software engineering society by providing a simple yet effective pre-processing approach to achieve equalized odds fairness in machine learning software.

• Fairness issues have attracted increasing attention since machine learning software is increasingly used for high-stakes and high-risk decisions.
• Amongst all the existing fairness notions, this work specifically targets "equalized odds" given its advantage in always allowing perfect classifiers.
• Equalized odds requires that members of every demographic group do not receive disparate mistreatment.