Inductive learning of fuzzy regression trees

Autoren Mario Drobics
Titel Inductive learning of fuzzy regression trees
Buchtitel Proc. 4th Conf. of the European Society for Fuzzy Logic and Technology and 11 Recontres Francophones sur al Logique Flou et ses Applications (EUSFLAT/LFA 2005)
Typ in Konferenzband
Ort Barcelona, Spain
ISBN 84-7653-872-3
Monat September
Jahr 2005
Seiten 16-21
SCCH ID# 509

In this paper we present a novel approach to data-driven fuzzy modeling which aims to create highly accurate but also easily comprehensible models. This goal is obtained by defining a flexible but expressive language automatically from the data. This language is then used to inductively learn fuzzy regression trees from the data. Finally, we present a detailed comparison study on the performance of the proposed method and an outlook to future developments.