Jan 6, 2025
A Multi-Objective Framework for Balancing Fairness and Accuracy in Debiasing Machine Learning Models. A Multi-Objective Framework for Balancing Fairne
Posted by Cecile G. Tamura in categories: information science, robotics/AI
Machine learning algorithms significantly impact decision-making in high-stakes domains, necessitating a balance between fairness and accuracy. This study introduces an in-processing, multi-objective framework that leverages the Reject Option Classification (ROC) algorithm to simultaneously optimize fairness and accuracy while safeguarding protected attributes such as age and gender.