• DocumentCode
    3250752
  • Title

    Neighborgram clustering. Interactive exploration of cluster neighborhoods

  • Author

    Berthold, Michael R. ; Wiswedel, Bemd ; Patterson, David E.

  • Author_Institution
    Data Anal. Res. Lab., Tripos Inc., South San Francisco, CA, USA
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    581
  • Lastpage
    584
  • Abstract
    We describe an interactive way to generate a set of clusters for a given data set. The clustering is done by constructing local histograms, which can then be used to visualize, select, and fine-tune potential cluster candidates. The accompanying algorithm can also generate clusters automatically, allowing for an automatic or semi-automatic clustering process where the user only occasionally interacts with the algorithm. We illustrate the ability to automatically identify and visualize clusters using NCI´s AIDS Antiviral Screen data set.
  • Keywords
    computational complexity; data analysis; pattern clustering; program visualisation; Neighborgrarn; clustering; data set; expert knowledge; interactive visualization; large data sets; local histograms; Algorithm design and analysis; Bioinformatics; Clustering algorithms; Data analysis; Data visualization; Greedy algorithms; Histograms; Pattern analysis; Prototypes; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on
  • Print_ISBN
    0-7695-1754-4
  • Type

    conf

  • DOI
    10.1109/ICDM.2002.1184004
  • Filename
    1184004