• DocumentCode
    2199243
  • Title

    An Efficient Algorithm for Multi-class Support Vector Machines

  • Author

    Guo, Jun ; Takahashi, Norikazu ; Hu, Wenxin

  • Author_Institution
    Comput. Center, East China Normal Univ., Shanghai
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    327
  • Lastpage
    331
  • Abstract
    A novel algorithm for multi-class support vector machines (SVMs) is proposed in this paper. The tree constructed in our algorithm consists of a series of two-class SVMs. Considering both separability and balance, in each iteration multi-class patterns are divided into two sets according to the distances between pairwise classes and the number of patterns in each class. This algorithm can well treat with the unequally distributed problems. The efficiency of the proposed method are verified by the experimental results.
  • Keywords
    distributed algorithms; iterative methods; support vector machines; multiclass patterns; multiclass support vector machines; pairwise classes; two-class SVMs; unequally distributed problems; Computer science; Machine learning; Pattern recognition; Quadratic programming; Support vector machine classification; Support vector machines; Testing; Tree graphs; Voting; algorithm; multi-class support vector machines; tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Theory and Engineering, 2008. ICACTE '08. International Conference on
  • Conference_Location
    Phuket
  • Print_ISBN
    978-0-7695-3489-3
  • Type

    conf

  • DOI
    10.1109/ICACTE.2008.48
  • Filename
    4736975