• DocumentCode
    1949383
  • Title

    Research on Combination Kernel Function of Support Vector Machine

  • Author

    Song, Huazhu ; Ding, Zichun ; Guo, Cuicui ; Li, Zhe ; Xia, Hongxia

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan
  • Volume
    1
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    838
  • Lastpage
    841
  • Abstract
    The kernel function and parameters selection is a key problem in the research of support vector machine. After discussing the influence of support vector machine on kernel parameters and error penalty factors, a new kernel function CombKer was proposed and constructed. The CombKer kernel function is a kind of combination kernel function, which combines the Gaussian RBF kernel function that has the local characteristic, with the linear kernel function that has the global characteristic. Finally, some experiments on different domains data in the support vector machine constructed by the CombKer kernel function were done, and the results showed the better ability on prediction of this kind of support vector machine and proved the validation of the CombKer kernel function.
  • Keywords
    Gaussian processes; radial basis function networks; support vector machines; CombKer combination kernel function; Gaussian RBF kernel function; error penalty factor; linear kernel function; parameter selection; support vector machine; Computer science; Kernel; Machine learning; Neural networks; Pattern analysis; Polynomials; Support vector machine classification; Support vector machines; Time series analysis; Virtual colonoscopy; Gaussian radial basis kernel function (RBF); Support Vector Machine (SVM); combination kernel function; linear kernel function;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.1231
  • Filename
    4721880