• DocumentCode
    447567
  • Title

    LEM2-based rule induction via clustering decision classes

  • Author

    Inuiguchi, Masahiro ; Tsurumi, Masayo ; Fukuda, Daisuke ; Yamanaka, Kazuki

  • Author_Institution
    Graduate Sch. of Eng. Sci., Osaka Univ., Japan
  • Volume
    3
  • fYear
    2005
  • fDate
    10-12 Oct. 2005
  • Firstpage
    2781
  • Abstract
    In this paper, it is proposed to cluster decision classes before applying a rule induction method. The similarity between decision classes is defined and an agglomerative hierarchical clustering method is applied. At each branch of the obtained dendrogram, LEM2, one of frequently used rule induction algorithm, is applied to induce decision rules inferring clusters. In such a way, a set of decision rules classifying objects into decision classes is obtained. The performance of the proposed method is compared with the direct application of LEM2 to each decision class by a numerical experiment.
  • Keywords
    data mining; decision theory; inference mechanisms; pattern classification; pattern clustering; LEM2 algorithm; agglomerative hierarchical clustering method; clustering decision classes; decision rules; rule induction method; Clustering algorithms; Clustering methods; Data analysis; Humans; Information analysis; Rough sets; Rough set; clustering; rule induction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2005 IEEE International Conference on
  • Print_ISBN
    0-7803-9298-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.2005.1571571
  • Filename
    1571571