• DocumentCode
    3213655
  • Title

    A Algorithm to Incremental Learning with Support Vector Machine and Its Application in Multi-class Classification

  • Author

    Zhao Ying ; Wan Fuyong

  • Author_Institution
    Dept. of Math., East China Normal Univ., Shanghai, China
  • fYear
    2006
  • fDate
    7-11 Aug. 2006
  • Firstpage
    1840
  • Lastpage
    1844
  • Abstract
    Support vector machine (SVM) is a new statistical learning method. By analyzing the theory and characteristics of SVM, this paper presents an algorithm of incremental learning. This algorithm is tested with multi-class classification and results show that this algorithm reduces the training time. Meanwhile, it keeps the testing accuracy.
  • Keywords
    learning (artificial intelligence); pattern classification; support vector machines; incremental learning; multiclass classification; statistical learning; support vector machine; Algorithm design and analysis; Electronic mail; IEEE catalog; Machine learning; Mathematics; Mercury (metals); Statistical learning; Support vector machine classification; Support vector machines; Testing; Incremental Learning; Multi-class Classification; Support Vector Machine (SVM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2006. CCC 2006. Chinese
  • Conference_Location
    Harbin
  • Print_ISBN
    7-81077-802-1
  • Type

    conf

  • DOI
    10.1109/CHICC.2006.280868
  • Filename
    4060416
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3213655