An incremental MaxSAT-based model to learn balanced rules

arXiv:2403.16418v1 Announce Type: new
Abstract: The increasing advancements in the field of machine learning have led to the development of numerous applications that effectively address a wide range of problems with accurate predictions. However, in certain cases, accuracy alone may not be sufficient. Many real-world problems also demand explanations and interpretability behind the predictions. One of the most popular interpretable models that are classification rules. This work aims to propose an incremental model for learning interpretable and balanced rules based …

abstract accuracy applications arxiv cases cs.ai cs.lg cs.lo demand development however incremental interpretability learn machine machine learning predictions rules type world