FS-LiRT - An inductive learning method for creating comprehensible fuzzy regression trees

M. Drobics. FS-LiRT - An inductive learning method for creating comprehensible fuzzy regression trees. number SCCH-TR-0507, 2005.

Autoren
  • Mario Drobics
TypTechnischer Bericht
NummerSCCH-TR-0507
Jahr2005
Abstract 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. The paper is closed with a detailed comparison study on the performance of the proposed method and an outlook to future developments.