Classification by ordinal sums of conjunctive and disjunctive functions for explainable AI and interpretable machine learning solutions

• Published in: Knowledge-based systems Vol. 220; p. 106916
• Main Authors: Hudec, Miroslav, Mináriková, Erika, Mesiar, Radko, Saranti, Anna, Holzinger, Andreas
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 23.05.2021; Elsevier Science Ltd
• Subjects: Agglomeration; Aggregation functions; Algorithms; Classification; Cognitive tasks; Domains; Explainable AI; Explainable artificial intelligence; Glass-box; Interactive ML; Interpretable Machine Learning (ML); Machine learning; Ordinal sums; Subject specialists; Sums; Transparency; Interpretable Machine Learning (ML); Transparency; Explainable AI; Interactive ML; Glass-box; Aggregation functions; Ordinal sums

We propose a novel classification according to aggregation functions of mixed behaviour by variability in ordinal sums of conjunctive and disjunctive functions. Consequently, domain experts are empowered to assign only the most important observations regarding the considered attributes. This has the...