文章基本信息

标题：Smooth Harmonic Transductive Learning
本地全文：下载
作者：Xie, Ying ; Luo, Bin ; Xu, Rongbin 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2013
卷号：8
期号：12
页码：3079-3085
DOI：10.4304/jcp.8.12.3079-3085
语种：English
出版社：Academy Publisher
摘要：In this paper, we present a novel semi-supervisedsmooth harmonic transductive learning algorithm that canget closed-form solution. Our method introduces the unlabeledclass information to the learning process and triesto exploit the similar configurations shared by the labeldistribution of data. After discovering the property ofsmooth harmonic function based on spectral clusteringin classification task, we design an adaptive thresholdingmethod for smooth harmonic transductive learning basedon classification error. The proposed adaptive thresholdingmethod can select the most suitable thresholds flexibly.Plentiful experiments on data sets show our proposed closedformsmooth harmonic transductive learning framework getexcellent improvement compared with two baseline methods.
关键词：harmonic function;transductive learning;adaptive threshold