作者机构：[Pan, Mei-Qin ;He, Guo-Ping ;Han, Cong-Ying ;Xue, Xin ] College of Information Science and Engineering, Shandong University of Science and Technology, 更多[Pan, Mei-Qin ;He, Guo-Ping ;Han, Cong-Ying ;Xue, Xin ] College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao 266510, China;[Xue, Xin ] Department of Mathematics, Taishan University, Tai'an 271000, China;[Shi, You-Qun ] College of Computer Science and Engineering, Donghua University, Shanghai 200051, China 收起
通讯作者：Pan, MQ
来源：Journal of Donghua University (English Edition)
出版年：2006
卷：23
期：6
页码：148-152
摘要：The model of optimization problem for Support Vector Machine(SVM) is provided, which based on the definitions of the dual norm and the distance between a point and its projection onto a given plane. The model of improved Support Vector Machine based on 1-norm (1-SVM) is provided from the optimization problem, yet it is a discrete programming. With the smoothing technique and optimality knowledge, the discrete programming is changed into a continuous programming. Experimental results show that the algorithm is easy to implement and this method can select and suppress the problem features more efficiently. Illustrative examples show that the 1-SVM deal with the linear or nonlinear classification well.
