DocumentCode
3257137
Title
A fuzzy classifier system that generates fuzzy if-then rules for pattern classification problems
Author
Ishibuchi, Hsao ; Nakashima, Tomoharu ; Murata, Tadahiko
Author_Institution
Dept. of Ind. Eng., Osaka Prefecture Univ., Japan
Volume
2
fYear
1995
fDate
29 Nov-1 Dec 1995
Firstpage
759
Abstract
We propose a fuzzy classifier system that can automatically generate fuzzy if-then rules from numerical data (i.e., from training patterns) for multi-dimensional pattern classification problems. Classifiers in our approach are fuzzy if-then rules such as “If x p1 is small and xp2 is large then classify xp as Class 2”. The proposed classifier system can find a compact rule set by attaching large fitness values to such fuzzy if-then rules that can correctly classify many training patterns. That is, only fuzzy if-then rules with large fitness values are selected to construct a compact fuzzy system with high classification performance
Keywords
fuzzy set theory; fuzzy systems; genetic algorithms; pattern classification; classification performance; compact rule set; fitness values; fuzzy classifier system; fuzzy if-then rules; fuzzy system; genetic algorithms; multidimensional pattern classification; numerical data; pattern classification; training patterns; Automatic control; Control systems; Fuzzy control; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Genetic algorithms; Humans; Industrial engineering; Pattern classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2759-4
Type
conf
DOI
10.1109/ICEC.1995.487481
Filename
487481
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