Authors
Hisao Ishibuchi, Tomoharu Nakashima, Tadahiko Murata
Publication date
1995/11/29
Conference
Proceedings of 1995 IEEE International Conference on Evolutionary Computation
Volume
2
Pages
759-764
Publisher
IEEE
Description
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/sub p1/ is small and x/sub p2/ is large then classify x/sub p/ 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.
Total citations
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Scholar articles
H Ishibuchi, T Nakashima, T Murata - Proceedings of 1995 IEEE International Conference on …, 1995