文献类型：会议论文

英文题名：Solution Path Algorithm for the Fuzzy Weighted Doubly Regularized Support Vector Machine

作者：Li, Juntao[1];Wang, Yadi[1];Cao, Yimin[1];Meng, Deyuan[2];Xiao, Huimin[3]

第一作者：Li, Juntao

通讯作者：Li, JT[1]

机构：[1]Henan Normal Univ, Sch Math & Informat Sci, Xinxiang 453007, Peoples R China;[2]Beihang Univ BUAA, Res Div 7, Beijing 100191, Peoples R China;[3]Henan Univ Econ & Law, Dept Math & Informat Sci, Zhengzhou 450002, Peoples R China

第一机构：Henan Normal Univ, Sch Math & Informat Sci, Xinxiang 453007, Peoples R China

通讯机构：[1]corresponding author), Henan Normal Univ, Sch Math & Informat Sci, Xinxiang 453007, Peoples R China.

会议论文集：27th Chinese Control and Decision Conference (CCDC)

会议日期：MAY 23-25, 2015

会议地点：Qingdao, PEOPLES R CHINA

语种：英文

外文关键词：Support vector machine; Solution path algorithm; Elastic net penalty; Hinge loss

摘要：A fuzzy weighted doubly regularized support vector machine for binary classification is proposed in this paper. Fuzzy weights are presented by using the distance information within each class. Then the fuzzy weighted doubly regularized support vector machine is proposed by combing the weighted hinge loss and the adaptive elastic net penalty. A reasonable correlation between two model parameters is also given and the solution path algorithm to compute the solution paths of the proposed support vector machine is developed. The simulation results on two data sets demonstrate the effectiveness of the proposed method.