• DocumentCode
    2919694
  • Title

    The Attribute Reduce with SAT Algorithm

  • Author

    Zhao, Qingshan ; Zheng, Xiaolong

  • Author_Institution
    Dept. of Comput., Shanxi Xinzhou Teachers Univ., Xinzhou, China
  • Volume
    3
  • fYear
    2009
  • fDate
    21-22 Nov. 2009
  • Firstpage
    23
  • Lastpage
    26
  • Abstract
    Rough set theory has been successfully applied to many areas including machine learning pattern recognition decision analysis process control, knowledge discovery from databases. An algorithm in finding minimal reduction based on prepositional satisfiability (abbreviated as SAT) algorithm is proposed. A branch and bound algorithm is presented to solve the proposed SAT problem. The experimental result shows that the proposed algorithm has significantly reduced the number of rules generated form the obtained reduction with high percentage of classification accuracy.
  • Keywords
    computability; rough set theory; tree searching; SAT algorithm; branch-and-bound algorithm; minimal attribute reduction; prepositional satisfiability; rough set theory; Algorithm design and analysis; Data analysis; Databases; Decision making; Information analysis; Information systems; Machine learning algorithms; Pattern analysis; Pattern recognition; Rough sets; SAt; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-0-7695-3859-4
  • Type

    conf

  • DOI
    10.1109/IITA.2009.347
  • Filename
    5369560