• DocumentCode
    1592495
  • Title

    A Method for Finding Implicating Rules Based on the Genetic Algorithm

  • Author

    Jun, Zhou ; Shu-You, Li ; Hong-Yan, Mei ; Hai-Xia, Liu

  • Author_Institution
    Liaoning Univ. of Technol., Dalian
  • Volume
    3
  • fYear
    2007
  • Firstpage
    400
  • Lastpage
    405
  • Abstract
    In information system, some rules have implicating relations (called implicating rules), but some rules have not. An approach of finding implicating rules based on the genetic algorithm is proposed. Some properties of independence and correlation of descriptions are discussed. It can obtain directly the implicating rules (including the positive and negative rules) with the correlation of two descriptions according to strength of implication defined in this paper. At the same time, an algorithm for finding optimized rules based on genetic algorithm is presented. By it, the problem of efficiency of finding rules is solved. At last, the efficiency and practicability of the method are illustrated by the experiment results.
  • Keywords
    data mining; genetic algorithms; rough set theory; data mining; genetic algorithm; implicating rules; information system; rough set theory; Artificial intelligence; Cognitive science; Computer science; Data analysis; Data mining; Genetic algorithms; Information systems; Learning systems; Machine learning; Set theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2007. ICNC 2007. Third International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2875-5
  • Type

    conf

  • DOI
    10.1109/ICNC.2007.61
  • Filename
    4344545