• DocumentCode
    2664110
  • Title

    New heuristic attribute reduction algorithm based on rough set

  • Author

    Weiwei, Fang ; Bingru, Yang ; Zheng, Peng

  • Author_Institution
    Inf. Eng. Sch., Univ. of Sci. & Technol. Beijing, Beijing
  • fYear
    2008
  • fDate
    16-18 July 2008
  • Firstpage
    285
  • Lastpage
    287
  • Abstract
    This paper summarized advantages and disadvantages of recent attribute reduction algorithms, and proposed a new attribute reduction method which is taken attribute correlation as heuristic information, this method can not only remove irrelevant features, but also delete redundant features from the candidate attribute set. Theoretical analysis and experiment results demonstrate that on the premise of unchanged classification precision, the algorithm can obtain the best attribute reduce set and has good feasibility.
  • Keywords
    data mining; rough set theory; data mining; heuristic attribute reduction algorithm; rough set; Algorithm design and analysis; Classification algorithms; Data mining; Glass; Heuristic algorithms; Information science; Voting; Attribute Reduction; Data mining; KDD; Rough Set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2008. CCC 2008. 27th Chinese
  • Conference_Location
    Kunming
  • Print_ISBN
    978-7-900719-70-6
  • Electronic_ISBN
    978-7-900719-70-6
  • Type

    conf

  • DOI
    10.1109/CHICC.2008.4605398
  • Filename
    4605398