• DocumentCode
    3424391
  • Title

    Decision rule extraction and reduction based on grey lattice classification

  • Author

    Yamaguchi, Daisuke ; Li, Guo-Dong ; Mizutani, Kozo ; Akabane, Takahiro ; Nagai, Masatake ; Kitaoka, Masatoshi

  • Author_Institution
    Kanagawa Univ., Japan
  • fYear
    2005
  • fDate
    15-17 Dec. 2005
  • Abstract
    This paper proposes a decision rule of extraction and reduction that is based on grey lattice classification. This proposal method comes from joining between rough set theory and grey theory as an approximation algorithm. Grey lattice operations are defined by combining interval grey number in grey theory with interval lattice operations in interval algebra. By defining the equivalents in interval grey number, given data space is correspondent to equivalents of rough set. This proposal method classifies each data set into 3-patterns from given training samples, as existing possibility class, newly made possibility class and existing necessity class. As given examples which require only necessity class, decision rule is simplified by a reduction procedure.
  • Keywords
    algebra; grey systems; learning (artificial intelligence); pattern classification; rough set theory; approximation algorithm; decision rule extraction; decision rule reduction; grey lattice classification; grey theory; interval algebra; interval grey number; interval lattice operations; rough set theory; Algebra; Classification tree analysis; Data mining; Educational institutions; Image recognition; Lattices; Pattern recognition; Principal component analysis; Proposals; Set theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
  • Print_ISBN
    0-7695-2495-8
  • Type

    conf

  • DOI
    10.1109/ICMLA.2005.19
  • Filename
    1607427