Boolean Rule

Boolean rules, representing logical combinations of features for classification or decision-making, are a focus of research aiming to create more interpretable and efficient machine learning models. Current work explores optimization techniques, such as mixed-integer programming and column generation, to generate optimal or near-optimal rule sets within various model architectures, including decision trees and rule-based systems. This research addresses the need for transparent and understandable AI systems, impacting fields ranging from healthcare and finance to legal tech, where interpretability and fairness are paramount.