关键词: 支持向量机, 单类支持向量机, 分类器

Abstract: One-Class Support Vector Machine（OCSVM） is an important and widely used classifier. It can be used in the context in which the negative samples are hardly collected or labeled, such as intrusion detection, fault detection and diagnosis, and the classification of remote sensing data. Therefore, OCSVM has been attracting more and more attention on its theory research and applications in recent years. This paper reviews the two important algorithms for OCSVM, followed by the improvements on those algorithms, including using the unlabeled samples, selecting certain samples, and modifying the optimization problems. It makes conclusion for OCSVM.

Key words: Support Vector Machine, One-Class Support Vector Machine, classifier