• DocumentCode
    1968051
  • Title

    Multi-output Support Vector Machine Regression and Its Online Learning

  • Author

    Gensheng, Hu ; Dong, Liang

  • Author_Institution
    Educ. Dept. Key Lab. of IC & SP, Anhui Univ., Hefei
  • Volume
    4
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    878
  • Lastpage
    881
  • Abstract
    This paper introduces multi-output support vector machine regression (M-SVR) by using the re-weight iterative algorithm. Then the problem of online learning of M-SVR is solved by given the iterative formula for the weight of regression function using the gradient descent algorithm of instantaneous risk. Computer experiments show that the accuracy and workload of the algorithm are superior to that using several one-dimensional output SVRs algorithm.
  • Keywords
    learning (artificial intelligence); regression analysis; support vector machines; multi-output regression; online learning; support vector machine; Computer science; Hilbert space; Iterative algorithms; Kernel; Laboratories; Machine learning; Paper technology; Software engineering; Statistical learning; Support vector machines; multi-output regression; online learning; support vector machine;
  • 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.2008.1024
  • Filename
    4722758
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1968051