• 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