Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (10): 2429-2433,2505.

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Robust support vector machine weighted by spatial rank depth

HU Yong-gang, WU Yi, LI Qiang   

  1. Dept. of Mathematics and System Science, National Univ. of Defense Technology, Changsha 410073, China
  • Received:2008-09-03 Revised:2008-11-03 Online:2009-10-20 Published:2010-01-03

Abstract: This paper presents a robust support vector machine(SVM) weighted by the spatial rank depth.According to the high sensitivity of SVM to the outliers,the regularization term is weighted by the data depth factor in order to adaptively reduce the influence on the classification by those outliers.The two dual forms of 1-norm and 2-norm depth weighted SVM(DWSVM) are deduced respectively,and the solution of depth in feature space is also presented.Compared with the method weighted by the distance to the mean center,this method is more robust than fuzzy SVM.

CLC Number: 

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