Title :
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
fDate :
6/24/1905 12:00:00 AM
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;
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
DOI :
10.1109/FUZZ.2002.1006715
