• DocumentCode
    1129733
  • Title

    Rule Weight Specification in Fuzzy Rule-Based Classification Systems

  • Author

    Ishibuchi, Hisao ; Yamamoto, Takashi

  • Author_Institution
    Dept. of Ind. Eng., Osaka Prefecture Univ., Japan
  • Volume
    13
  • Issue
    4
  • fYear
    2005
  • Firstpage
    428
  • Lastpage
    435
  • Abstract
    This paper shows how the rule weight of each fuzzy rule can be specified in fuzzy rule-based classification systems. First, we propose two heuristic methods for rule weight specification. Next, the proposed methods are compared with existing ones through computer simulations on artificial numerical examples and real-world pattern classification problems. Simulation results show that the proposed methods outperform the existing ones in the case of multiclass pattern classification problems with many classes.
  • Keywords
    data mining; fuzzy reasoning; fuzzy set theory; knowledge based systems; pattern classification; data mining; fuzzy rule based classification system; heuristic method; multiclass pattern classification; rule weight specification; Association rules; Computational modeling; Computer simulation; Data mining; Degradation; Fuzzy sets; Fuzzy systems; Industrial engineering; Knowledge based systems; Pattern classification; Data mining; fuzzy systems; pattern classification; rule generation; rule selection;
  • fLanguage
    English
  • Journal_Title
    Fuzzy Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6706
  • Type

    jour

  • DOI
    10.1109/TFUZZ.2004.841738
  • Filename
    1492396