DRST: Data-Driven Consistent Discretization with Rough Sets

This presentation explores the DRST methodology, addressing challenges in discretization with a focus on decision consistency. It integrates Rough Set Theory and K-means clustering for interval optimization, detailing natural interval formation, adaptive refinements, and dependency measures. Case studies highlight DRST's efficacy compared to traditional methods and its impact on decision quality. We conclude by identifying benefits, computational considerations, and avenues for future...