• DocumentCode
    390406
  • Title

    Pre-extracting support vector by adaptive projective algorithm

  • Author

    Ai-ling, Ding ; Fang, Liu ; Ying Li

  • Author_Institution
    Comput. Sch., Xidian Univ., Xi´´an, China
  • Volume
    1
  • fYear
    2002
  • fDate
    26-30 Aug. 2002
  • Firstpage
    21
  • Abstract
    A new method, called adaptive projective algorithm, which is able to extract support vectors from given training examples, is put forward as a support vector algorithm. The method greatly reduces the training samples and so improves the speed of the support vector machine, while the ability of the support vector machine in pattern classification is unaffected: Our experimental results show remarkable improvement of speed to support our idea.
  • Keywords
    adaptive signal processing; iterative methods; learning (artificial intelligence); learning automata; optimisation; pattern classification; adaptive projective algorithm; iterative method; optimization; pattern classification; support vector algorithm; support vector machine; training examples; Data mining; Erbium; Iterative algorithms; Iterative methods; Pattern classification; Risk management; Support vector machine classification; Support vector machines; Training data; Upper bound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2002 6th International Conference on
  • Print_ISBN
    0-7803-7488-6
  • Type

    conf

  • DOI
    10.1109/ICOSP.2002.1180973
  • Filename
    1180973