标题：Study on support vector machine based on 1-norm
作者：Pan, Mei-Qin ;He, Guo-Ping ;Han, Cong-Ying ;Xue, Xin ;Shi, You-Qun
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
来源：Journal of Donghua University (English Edition)
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.