• DocumentCode
    3288114
  • Title

    Decision tree SVM basing on kernel clustering

  • Author

    Zhang, Jianhua

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
  • fYear
    2011
  • fDate
    15-17 April 2011
  • Firstpage
    5791
  • Lastpage
    5794
  • Abstract
    Basing on the SVM that is used to solve pattern recognition problems, this paper brings up a new pattern recognition method that combines the kernel K-means Clustering with decision tree SVM. And this method is simpler structure and higher computational efficiency than old one. Meanwhile, this method achieves a good result in the experiment.
  • Keywords
    decision trees; pattern clustering; support vector machines; computational efficiency; decision tree SVM; kernel k-means clustering; pattern recognition; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Decision trees; Kernel; Pattern recognition; Support vector machines; Decision tree; Kernel K-means Clustering; Multi-class pattern recognition; SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Information and Control Engineering (ICEICE), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-8036-4
  • Type

    conf

  • DOI
    10.1109/ICEICE.2011.5778022
  • Filename
    5778022
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3288114