• DocumentCode
    3324754
  • Title

    Research on new data mining method based on hybrid genetic algorithm

  • Author

    Lianmei, Zhang ; Xingjun, Jiang

  • Author_Institution
    Comput. Sch., Wuhan Univ., Wuhan, China
  • Volume
    1
  • fYear
    2010
  • fDate
    5-7 May 2010
  • Firstpage
    462
  • Lastpage
    465
  • Abstract
    For classification problems in data mining based on the thought of combination classification method, this paper proposes a combination classification method of multiple decision trees, which was based on genetic algorithm. In the proposed combination classification method, multiple decision trees that adopt the method of probability measurement level output are parallel combined. Then genetic algorithm is used for the optimization of connection weight matrix in combination algorithm. Further more, two sets of simulation experiment data are used to test and evaluate the proposed combination classification method. Results of the experiments indicate that the proposed combination classification method has higher classification accuracy level than single decision tree. Moreover, it optimizes classification rules and sustains good interpretability for classification results.
  • Keywords
    data mining; decision trees; genetic algorithms; classification accuracy; combination classification method; connection weight matrix; data mining method; decision tree; hybrid genetic algorithm; probability measurement level output; Automatic control; Bayesian methods; Classification tree analysis; Communication system control; Data mining; Decision trees; Genetic algorithms; Radio control; Testing; Voting; combination method; formatting; genetic algorithm; insert (key words) data mining; multiple decision trees; style; styling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Communication Control and Automation (3CA), 2010 International Symposium on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4244-5565-2
  • Type

    conf

  • DOI
    10.1109/3CA.2010.5533761
  • Filename
    5533761