文献类型：期刊文献

英文题名：ν-Nonparallel support vector machine for pattern classification

作者：Tian, Yingjie[1]; Zhang, Qin[1]; Liu, Dalian[2]

第一作者：Tian, Yingjie

通讯作者：Liu, Dalian

机构：[1] Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, 100190, China; [2] Department of Basic Course Teaching, Beijing Union University, Beijing, 100101, China

第一机构：Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, 100190, China

年份：2014

卷号：25

期号：5

起止页码：1007-1020

外文期刊名：Neural Computing and Applications

收录：EI(收录号：20143600013384)

语种：英文

外文关键词：Classification (of information) - Support vector machines - Vectors

摘要：In this paper, we propose a novel nonparallel hyperplane classifier, named ν-nonparallel support vector machine (ν-NPSVM), for binary classification. Based on our recently proposed method, i.e., nonparallel support vector machine (NPSVM), which has been proved superior to the twin support vector machines, ν-NPSVM is parameterized by the quantity ν to let ones effectively control the number of support vectors. By combining the ν-support vector classification and the ν-support vector regression together to construct the primal problems, ν-NPSVM inherits the advantages of ν-support vector machine so that enables us to eliminate one of the other free parameters of the NPSVM: the accuracy parameter Ε and the regularization constant C. We describe the algorithm, give some theoretical results concerning the meaning and the choice of ν, and also report the experimental results on lots of data sets to show the effectiveness of our method. ? 2014, Springer-Verlag London.