• DocumentCode
    1644014
  • Title

    A novel two level evolutionary approach For classification rules extraction

  • Author

    Baba-ali, Ahmed Riadh

  • Author_Institution
    LRPE Lab., Univ. of Sci. & Technol. Houari Boumediene, Algiers
  • fYear
    2009
  • Firstpage
    3306
  • Lastpage
    3313
  • Abstract
    In this paper, we present a description of our research in the field of data mining. We describe a two level hybrid evolutionary approach for classification rule extraction. Our method is a mix of two classic approaches called respectively Michigan and Pittsburg approaches. The goal is to take advantage of both approaches while minimising their drawbacks. The result has been compared favourably to classical approaches.
  • Keywords
    data mining; evolutionary computation; pattern classification; classification rules extraction; data mining; hybrid evolutionary approach; two level evolutionary approach; Data mining; Databases; Evolutionary computation; Genetic algorithms; Humans; Laboratories; Neural networks; Predictive models; Robustness; Testing; Knowledge extraction; classification; data mining; evolutionary algorithms; hybrid metaheuristic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983364
  • Filename
    4983364