• DocumentCode
    1661435
  • Title

    A possibilistic type of alternative fuzzy c-means

  • Author

    Yang, Minn-Shen ; Wu, Kuo-Lung

  • Author_Institution
    Dept. of Math., Chung Yuan Christian Univ., Chung-li, Taiwan
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1456
  • Lastpage
    1459
  • Abstract
    The alternative fuzzy c-means (AFCM) clustering algorithm proposed by Wu and Yang (2001) has shown more robustness than the fuzzy c-means (FCM) on the basis of the robust statistic and the influence function. We propose a possibilistic type of AFCM by relaxing the restriction Σi=1c μi(x)=1 for all data points x. The resulting cluster memberships constitute a possibilistic partition which is different to a fuzzy partition from AFCM. The comparisons of the proposed method to FCM, AFCM and possibilistic c-means are made
  • Keywords
    fuzzy set theory; pattern clustering; possibility theory; cluster memberships; clustering algorithm; influence function; possibilistic alternative fuzzy c-means; possibilistic partition; robust statistic; Capacitive sensors; Clustering algorithms; Equations; Fuzzy sets; Mathematics; Partitioning algorithms; Phase change materials; Power generation; Robustness; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7280-8
  • Type

    conf

  • DOI
    10.1109/FUZZ.2002.1006719
  • Filename
    1006719