• DocumentCode
    2335920
  • Title

    Incremental learning with support vector machines

  • Author

    Rüping, Stefan

  • Author_Institution
    Dept. of Comput. Sci., Dortmund Univ., Germany
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    641
  • Lastpage
    642
  • Abstract
    Support vector machines (SVMs) have become a popular tool for machine learning with large amounts of high dimensional data. In this paper an approach for incremental learning with support vector machines is presented, that improves the existing approach of Syed et al. (1999). An insight into the interpretability of support vectors is also given
  • Keywords
    learning (artificial intelligence); learning automata; high dimensional data; incremental learning; machine learning; support vector machines; Artificial intelligence; Computer science; Machine learning; Robustness; Support vector machines; Testing; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    0-7695-1119-8
  • Type

    conf

  • DOI
    10.1109/ICDM.2001.989589
  • Filename
    989589
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2335920