• DocumentCode
    1934158
  • Title

    A New Fuzzy Multicategory Support Vector Machines Classifier

  • Author

    Lu, Shu-xia ; Liu, Xian-Hao ; Zhai, Jun-hai

  • Volume
    5
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    2859
  • Lastpage
    2862
  • Abstract
    This paper proposes a new fuzzy multicategory support vector machines (FMSVM) classifier. The main idea is that the proposed FMSVM uses knowledge of the ambiguity associated with the membership of samples for a given class and the relative location of samples to the origin. Compared with the existing SVMs, the new proposed FMSVM that uses the L2-norm in the objective function has the improvement in aspects of classification accuracy and reducing the effects of noises and outliers.
  • Keywords
    fuzzy set theory; pattern classification; support vector machines; L2-norm; fuzzy multicategory classifier; support vector machines; Computer science; Cybernetics; Electronic mail; Fuzzy sets; Machine learning; Mathematics; Noise reduction; Research and development; Support vector machine classification; Support vector machines; Fuzzy membership; Multicategory classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370635
  • Filename
    4370635
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1934158