• DocumentCode
    3168442
  • Title

    A Fuzzy c-means Algorithm Based on an Adaptive L2 Minkowsky Distance

  • Author

    Cavalcanti, Nicomedes L.

  • Author_Institution
    Centro de Informatica - CIn / UFPE, Brazil
  • fYear
    2005
  • fDate
    6-9 Nov. 2005
  • Firstpage
    104
  • Lastpage
    109
  • Abstract
    An extension of the fuzzy c-means clustering algorithm based on an adaptive distance is presented. The proposed method furnishes a fuzzy partition and a prototype for each cluster by optimizing a criterion based on an adaptive L2 Minkowsky distance that changes at each algorithm’s iteration. Experiments with real and synthetic data sets show the usefulness of this method.
  • Keywords
    Clustering algorithms; Data analysis; Functional analysis; Heuristic algorithms; Iterative algorithms; Multidimensional systems; Optimization methods; Partitioning algorithms; Pattern recognition; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hybrid Intelligent Systems, 2005. HIS '05. Fifth International Conference on
  • Print_ISBN
    0-7695-2457-5
  • Type

    conf

  • DOI
    10.1109/ICHIS.2005.5
  • Filename
    1587734
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3168442