• DocumentCode
    1564669
  • Title

    A novel cluster validity criterion for fuzzy c-regression model clustering algorithm

  • Author

    Kung, Chung-Chun ; Hung, Jui-Chun

  • Author_Institution
    Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan
  • Volume
    2
  • fYear
    2003
  • Firstpage
    1368
  • Abstract
    This paper proposes a novel cluster validity criterion for the fuzzy c-regression model (FCRM) clustering algorithm. The goal of the proposed cluster validity criterion is to decide the appropriate number of clusters in a FCRM. The simulation results demonstrate its validness and effectiveness.
  • Keywords
    fuzzy set theory; least squares approximations; pattern clustering; statistical analysis; FCRM; effectiveness; fuzzy c-regression model clustering algorithm; novel cluster validity criterion; simulation results; validness; Algorithm design and analysis; Clustering algorithms; Data mining; Electronic mail; Entropy; Fuzzy systems; Image recognition; Partitioning algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
  • Print_ISBN
    0-7803-7810-5
  • Type

    conf

  • DOI
    10.1109/FUZZ.2003.1206630
  • Filename
    1206630
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1564669