• DocumentCode
    2458732
  • Title

    Evaluation of Clusterings -- Metrics and Visual Support

  • Author

    Achtert, Elke ; Goldhofer, Sascha ; Kriegel, Hans-Peter ; Schubert, Erich ; Zimek, Arthur

  • Author_Institution
    Inst. for Inf., Ludwig-Maximilians-Univ. Munchen, München, Germany
  • fYear
    2012
  • fDate
    1-5 April 2012
  • Firstpage
    1285
  • Lastpage
    1288
  • Abstract
    When comparing clustering results, any evaluation metric breaks down the available information to a single number. However, a lot of evaluation metrics are around, that are not always concordant nor easily interpretable in judging the agreement of a pair of clusterings. Here, we provide a tool to visually support the assessment of clustering results in comparing multiple clusterings. Along the way, the suitability of a couple of clustering comparison measures can be judged in different scenarios.
  • Keywords
    data visualisation; pattern clustering; clustering evaluation; evaluation metrics; multiple clusterings; visual support; Clustering algorithms; Complexity theory; Conferences; Data visualization; Measurement; Noise; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering (ICDE), 2012 IEEE 28th International Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1063-6382
  • Print_ISBN
    978-1-4673-0042-1
  • Type

    conf

  • DOI
    10.1109/ICDE.2012.128
  • Filename
    6228189