A novel SVR parameter selection base on bi-level programming problem

Authors:
Feng Xiangdong;Hu Guanghua
Affiliations:
School of Mathematics and Statistics of Yunnan University, Yunnan, Kunming, P.R. China and The Engineering & technical College of Chengdu University of Technology, Sichuan, Leshan, P.R. China;School of Mathematics and Statistics of Yunnan University, Yunnan, Kunming, P.R. China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

The selection of parameters plays an important role to the performance of support vector regression (SVR). In this paper, a novel parameter selection method for SVR is presented based on the bi-level programming problem. The proposed method does not need priori knowledge the value of the parametere Ɛ. At the same time, the parametere Ɛ can be calculated by the new SVR. And the number of the support vector will be controlled by the parameter C, even if the value of the parameter C is too big, the regression function still adapts to real function. And then, the complexity doesn't increase. Experimental results show that the better performance could be obtained by using the new SVR than the standard SVR.