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| SVR with Adaptive Error Penalization |
| Chen Xiao-feng①; Wang Shi-tong①; Cao Su-qun①② |
①School of Information, Southern Yangtz University, Wuxi 214122, China;
②Department of Mechanical Engineering, Huaiyin Institute of Technology, Huaian 223001, China |
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Abstract A novel support vector regression method AEPSVR is proposed in this paper. First, an approximate regression function is obtained using -SVR method, and then a new adaptive error penalization function is introduced to enhance the robust performance of SVR such that a robust support vector regression is derived. Because the proposed AEPSVR here is based on -SVR, so various optimization methods for SVR can be used. Experimental results show that the proposed AEPSVR can reduce the affect of outliers, and have the very good generalization capability.
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Received: 20 July 2006
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2008, Vol. 30 
