• DocumentCode
    950620
  • Title

    Improved possibilistic C-means clustering algorithms

  • Author

    Zhang, Jiang-She ; Leung, Yiu-Wing

  • Author_Institution
    Dept. of Inf. Sci., Xi´´an Jiaotong Univ., China
  • Volume
    12
  • Issue
    2
  • fYear
    2004
  • fDate
    4/1/2004 12:00:00 AM
  • Firstpage
    209
  • Lastpage
    217
  • Abstract
    A possibilistic approach was proposed in a previous paper for C-means clustering, and two algorithms realizing this approach were reported in two previous papers. Although the possibilistic approach is sound, these two algorithms tend to find identical clusters. In this paper, we modify and improve these algorithms to overcome their shortcoming. The numerical results demonstrate that the improved algorithms can determine proper clusters and they can realize the advantages of the possibilistic approach.
  • Keywords
    pattern clustering; possibility theory; C-means clustering; possibilistic approach; Acoustic noise; Clustering algorithms; Computer science; Information science; Partitioning algorithms; Prototypes; Research and development; Robustness;
  • fLanguage
    English
  • Journal_Title
    Fuzzy Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6706
  • Type

    jour

  • DOI
    10.1109/TFUZZ.2004.825079
  • Filename
    1284323