• DocumentCode
    1273726
  • Title

    Dynamic estimation of number of clusters in data sets

  • Author

    Boudraa, A.O.

  • Author_Institution
    Univ. de Paris-Nord, Villetaneuse, France
  • Volume
    35
  • Issue
    19
  • fYear
    1999
  • fDate
    9/16/1999 12:00:00 AM
  • Firstpage
    1606
  • Lastpage
    1608
  • Abstract
    A new method for estimating during clustering the number of clusters in data sets is proposed. The cluster validity index, Bcrit, takes the homogeneity in each cluster into account and is connected to the geometrical properties of the data set. Bcrit represents the combination of two validity indices. Comparisons between Bcrit and six cluster validity indices, conducted on real data sets, are presented
  • Keywords
    data compression; pattern clustering; unsupervised learning; cluster validity index; clusters; data sets; dynamic estimation; geometrical properties; homogeneity; validity indices;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19991151
  • Filename
    807011
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1273726