• DocumentCode
    2547656
  • Title

    Clustering algorithm on high-dimension data partitional mended attribute

  • Author

    Zhan, Tangsen ; Zhou, Yuanguo

  • Author_Institution
    Sch. of Inf. Eng., Jingdezhen Ceramica Inst., Jingdezhen, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    676
  • Lastpage
    678
  • Abstract
    In this paper, a clustering algorithm on high-dimension data partitional mended attribute is put foreword. First of all, through partition of the attribute value and discriminant degree of element, Conjunctive discriminant rules on training set are got. secondly, different discriminant rules on base of mended attribute are found. Experimental results show: the judgement rules got through the training set can better discriminate the test set. thereby, Experimental results verify the effectiveness of the proposed algorithm.
  • Keywords
    pattern clustering; clustering algorithm; conjunctive discriminant rules; discriminant degree of element; discriminant rules; high-dimension data partitional mended attribute; judgement rules; training set; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Data mining; Partitioning algorithms; Statistical analysis; Training; discriminant rules; distinguished degree; mended attribute; partitional interzone;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
  • Conference_Location
    Sichuan
  • Print_ISBN
    978-1-4673-0025-4
  • Type

    conf

  • DOI
    10.1109/FSKD.2012.6234074
  • Filename
    6234074