A fuzzy rule-based system for ensembling classification systems

Author

Nakashima, Tomoharu ; Nakai, Gaku ; Ishibuchi, Hisao

Author_Institution

Dept. of Ind. Eng., Osaka Prefecture Univ., Japan

Volume

2

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

1432

Lastpage

1437

Abstract

In this paper, we propose an ensembling method for pattern classification problems. The characteristic feature of our ensembling method is that two different types of fuzzy rule-based systems are used. One is a fuzzy rule-based classification system that suggests a class of an input pattern. The other is a fuzzy rule-based ensembling system that assigns a weight to the suggested class by each classification system. Our ensembling method consists of one fuzzy rule-based ensembling system, several fuzzy rule-based classification systems, and a gating node that finally determines the final classification of the input pattern. Computer simulations show the effectiveness of our ensembling method

Keywords

fuzzy logic; knowledge based systems; pattern classification; uncertainty handling; virtual machines; class weight assignment; computer simulations; ensembling method; fuzzy rule-based classification systems; fuzzy rule-based ensembling system; gating node; input pattern class suggestion; pattern classification problems; Automatic control; Computer simulation; Fuzzy control; Fuzzy systems; Industrial engineering; Knowledge based systems; Neural networks; Pattern classification; Training data; Voting;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-7280-8

Type

conf

DOI

10.1109/FUZZ.2002.1006715

Filename

1006715