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A fuzzy classifier system that generates fuzzy if-then rules for pattern classification problems

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3 Author(s)
Ishibuchi, H. ; Dept. of Ind. Eng., Osaka Prefecture Univ., Japan ; Nakashima, T. ; Murata, T.

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

Published in:

Evolutionary Computation, 1995., IEEE International Conference on  (Volume:2 )

Date of Conference:

29 Nov-1 Dec 1995