• DocumentCode
    658605
  • Title

    Kernel Based Simple Regularized Multiple Criteria Linear Programs for Binary Classification

  • Author

    Xi Zhao ; Lingfeng Niu ; Yong Shi

  • Author_Institution
    Univ. of Chinese Acad. of Sci., Beijing, China
  • Volume
    3
  • fYear
    2013
  • fDate
    17-20 Nov. 2013
  • Firstpage
    58
  • Lastpage
    61
  • Abstract
    Binary classification is the simplest case for classification problem. In this paper, we proposed a new kernel based regularized multiple criteria linear programs for binary classification. Modeling capability of original regularized model were improved by introducing nonlinear kernel, which made the model could identify nonlinear patterns in data. Experiments result showed our model is comparable with classical binary classifiers and suitable for real world application.
  • Keywords
    linear programming; pattern classification; binary classification; classical binary classifiers; kernel based regularized multiple criteria linear programs; kernel based simple regularized multiple criteria linear programs; modeling capability; nonlinear kernel; nonlinear patterns; original regularized model; Data mining; Data models; Kernel; Linear programming; Mathematical model; Optimization; Static VAr compensators; Binary Classification; Multiple Criteria Linear Programs; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013 IEEE/WIC/ACM International Joint Conferences on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4799-2902-3
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2013.150
  • Filename
    6690694