The article introduces the FRRI algorithm, combining fuzzy and rough set theory for rule induction. It highlights the importance of interpretability in machine learning and the need for white box models. The QuickRules algorithm is discussed as a predecessor to FRRI, showing improvements in rule induction methods. FRRI is introduced as a novel algorithm focusing on accuracy and concise rule creation. The paper outlines the theoretical background, the FRRI algorithm explanation, experimental evaluation, and comparison with other state-of-the-art rule induction approaches.
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arxiv.org
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