• DocumentCode
    510026
  • Title

    A Novel Solution Scheme for the Kernel MSE Model

  • Author

    Wang Jinghua

  • Author_Institution
    Shenzhen Grad. Sch., Univ. Town of Shenzhen, Shenzhen, China
  • Volume
    2
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    375
  • Lastpage
    378
  • Abstract
    In this paper we first show that the minimum squared-error solutions of kernel minimum squared-error (KMSE) models are neither unique nor numerically stable. We then propose a novel scheme for KMSE. This solution scheme can produce the unique solution and the maximum between-class margin. This solution has a highly accurate classification rate. The experimental result illustrates the feasibility and effectiveness of MNMSE solution of KMSE.
  • Keywords
    least mean squares methods; kernel minimum squared-error model; minimum squared-error solution; Artificial intelligence; Cities and towns; Computational complexity; Computational intelligence; Equations; Kernel; Pattern recognition; Transforms; Kernel minimum squared error; Modelling; Pattern Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.302
  • Filename
    5375805