计算机工程与应用Issue(15)：177-180,4.DOI:10.3778/j.issn.1002-8331.1208-0235
扩展约束的半监督谱聚类算法研究
Research of constraints-expansion semi-supervised spectral clustering algorithm
摘要
Abstract
Based on several typical clustering algorithm analysis and comparison, this paper proposes a new clustering based on constraint expansion(CESSC). This algorithm expands the known constraints set, changes the similarity relation of the sample points through the density-sensitive path distance, and then combines with semi-supervised spectral clustering to cluster. Experimental results on UCI benchmark data sets prove that CESSC algorithm has good clustering effect.关键词
半监督学习/成对约束/半监督谱聚类/距离矩阵Key words
semi-supervised learning/pair-wise constraint/semi-supervised spectral clustering/distance matrix分类
信息技术与安全科学引用本文复制引用
孙光辉,潘梅森..扩展约束的半监督谱聚类算法研究[J].计算机工程与应用,2014,(15):177-180,4.基金项目
湖南省科技厅项目（No.2010GK3021）。 （）
