A Modified Self-training Semi-supervised SVM Algorithm

摘要：

In this paper, we present a modified self-training semi-supervised SVM algorithm. In order to demonstate its validity and effectiveness, we carry out some experiments which prove that our method is better than the former algorithm. Using our modified self-training semi-supervised SVM algorithm, we can save much time for lableling the unlabelled data.

关键词： semi-supervised learning self-training SVM UCI

作者: Yun Jin Yong Ma Yun Jin Li Zhao

作者单位: School of Physics and Electronic EngineeringXuzhou Normal UniversityXuzhou, China Key Laboratory of Child Development and Learning Science of Ministry of Education Southeast Universi Key Laboratory of Child Development and LearningScience of Ministry of EducationSoutheast University

会议类型: 国际会议

会议名称: 2011 International Conference on Information System and Computational Intelligence(2011 IEEE信息系统与计算智能国际会议 ICISCI 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 458-461

在线出版日期: 2011-01-18（万方平台首次上网日期，不代表论文的发表时间）