Linear programming ν-nonparallel support vector machine and its application in vehicle recognition

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• 作者：Guang-yu Zhu^a ; ^b ; ^{gyzhu@bjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Chen-guang Yang^a ; ^b ; ^{10214077@bjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Peng Zhang^c ; ^{zhangp@bjtrc.org.cn" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Classification ; Support vector machine ; Vehicle recognition ; Nonparallel ; Linear programming
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：26 November 2016
• 年：2016
• 卷：215
• 期：Complete
• 页码：212-216
• 全文大小：332 K

文摘

In this paper, based on the nonparallel hyperplane classifier, ν-nonparallel support vector machine (ν-NPSVM), we proposed its linear programming formulation, termed as ν-LPNPSVM. ν-NPSVM which has been proved superior to the twin support vector machines (TWSVMs), is parameterized by the quantity ν to let ones effectively control the number of support vectors. Compared with the quadratic programming problem of ν-NPSVM, the 1-norm regularization term is introduced to ν-LPNPSVM to make it to be linear programming problem which can be solved fastly and easily. We also introduce kernel functions directly into the formulation for the nonlinear case. The numerical experiments on lots of data sets verify that our ν-LPNPSVM is superior to TWSVMs and faster than standard NPSVMs. We also apply this new method to the vehicle recognition problem and justify its efficiency.