Catalina M. Jaramillo

BiasQD-DT: Creating Interpretable Trade-Offs in Classifier Bias with Quality-Diversity Optimization via Decision Trees

A novel framework that integrates evolved decision trees generated from random seed-based vectors and Quality Diversity (QD) optimization to jointly address decision interpretability, predictive performance, and fairness is proposed.