• DocumentCode
    1898763
  • Title

    An Approximate Attribute Reduction of Rough Set and Its Algorithm

  • Author

    Jin-Biao, Shen ; Yue-jin, Lv ; Duo-Xiu, Tao

  • Author_Institution
    Sch. of Math. & Inf. Sci., Guangxi Univ., Nanning, China
  • Volume
    2
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    591
  • Lastpage
    594
  • Abstract
    In view of the deficiencies of attribute reduction in classic rough set, On condition that knowledge classification ability remains basically unchanged, this paper renders a new definition of the approximate attribute reduction of rough set and discuss its nature and algorithms. Theory proves that approximate attribute reduction is an extension of the traditional attribute reduction. Finally, a concrete example demonstrates the feasibility and effectiveness of approximate attribute reduction dealing with ambiguity and uncertainty of knowledge in information systems.
  • Keywords
    approximation theory; pattern classification; rough set theory; approximate attribute reduction; information systems; knowledge classification ability; rough set; Automation; Concrete; Helium; Information science; Information systems; Mathematics; Rough sets; Set theory; Sufficient conditions; Uncertainty; approximate attribute reduction; reduction algorithm; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.377
  • Filename
    5287751