文献类型：期刊文献

英文题名：A kernel-based matrixzed one-class support vector machine

作者：Chen, Yanyan[1]; Yuan, June[1]; Hu, Zhengkun[1]

第一作者：陈艳燕

通讯作者：Chen, Yanyan

机构：[1] College of Applied Science and Technology, Beijing Union University, Beijing, 100101, China

第一机构：北京联合大学应用科技学院

年份：2016

卷号：9

期号：11

起止页码：381-390

外文期刊名：International Journal of Hybrid Information Technology

收录：EI(收录号：20165103134014)

语种：英文

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

摘要：One-class support vector machine (OCSVM) is an important and efficient classifier used when only one class of data is available while others are too expensive or difficult to collect. It uses vector as input data, and trains a linear or nonlinear decision function in vector space. However, the traditional vector-based classifiers may fail when input is matrix. Therefore, it makes sense to study matrixzed classifiers which can make use of the structural information presented in the data. In this paper we propose a matrix-based one-class classification algorithm named Kernel-based Matrixzed One-class Support Vector Machine (KMatOCSVM). It aims to convert the OCSVM to suit for matrix representation data and to deal with nonlinear one-class classification problems. The efficiency and validity of the proposed method is illustrated by four real-world matrixbased human face datasets. ? 2016 SERSC.