Antonio Berlanga de Jesús

Multi-Objective Minimal Feature Selection for Explainable-by-Design Classification: Equivalence-Aware Selection and Rashomon-Set Analysis Across Six Domains

High-stakes and regulated decision-support systems require predictive models that are simultaneously accurate and interpretable, yet accuracy is frequently obtained through opaque models whose behaviour is difficult to audit. This paper develops an explainable-by-design classification framework in which interpretabilit...