Chapter

Neural Information Processing

Volume 4232 of the series Lecture Notes in Computer Science pp 773-781

A Heuristic Weight-Setting Algorithm for Robust Weighted Least Squares Support Vector Regression

  • Wen WenAffiliated withCollege of Computer Science and Engineering, South China University of Technology
  • , Zhifeng HaoAffiliated withNational Mobile Communications Research Laboratory, Southeast University NanjingSchool of Mathematical Science, South China University of Technology
  • , Zhuangfeng ShaoAffiliated withSchool of Mathematical Science, South China University of Technology
  • , Xiaowei YangAffiliated withSchool of Mathematical Science, South China University of TechnologyFaculty of Information Technology, University of Technology,Sydney
  • , Ming ChenAffiliated withNational Mobile Communications Research Laboratory, Southeast University Nanjing

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Abstract

Firstly, a heuristic algorithm for labeling the “outlierness” of samples is presented in this paper. Then based on it, a heuristic weight-setting algorithm for least squares support vector machine (LS-SVM) is proposed to obtain the robust estimations. In the proposed algorithm, the weights are set according to the changes of the observed value in the neighborhood of a sample’s input space. Numerical experiments show that the heuristic weight-setting algorithm is able to set appropriate weights on noisy data and hence effectively improves the robustness of LS-SVM.