• DocumentCode
    1750665
  • Title

    Fuzzy cluster analysis of classified data

  • Author

    Timm, Heiko

  • Author_Institution
    Dept. of Knowledge Process. & Language Eng., Otto-von-Guericke-Univ. Magdeburg, Germany
  • Volume
    3
  • fYear
    2001
  • fDate
    25-28 July 2001
  • Firstpage
    1431
  • Abstract
    Fuzzy cluster analysis is a method for unsupervised clustering. However sometimes class information is available for the given dataset, i.e., only the number of clusters per class is unknown. In this paper it is discussed how class information can be exploited. Some common approaches are reviewed and a new approach is suggested, which integrates class information into fuzzy cluster analysis
  • Keywords
    fuzzy logic; image classification; pattern clustering; classified data; fuzzy cluster analysis; unsupervised clustering; Clustering algorithms; Data analysis; Humans; Information analysis; Knowledge engineering; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-7078-3
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2001.943759
  • Filename
    943759
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1750665