Automatic spectral clustering and its application

摘要：

An new algorithm called automatic spectral clustering (ASC) is proposed based on eigengap and orthogonai eigenvectnr in this paper. It mainly focuses on how to automatically determine the suitable class number in clustering and explores some intrinsic characteristics of the spectral clustering method. The proposed method firstly constructs the affinity matrix of data and carries on eigen-decomposition, then determine the class number according to the eigengap. Finally, the data are classified by employing the angle between two eigenvectors. The experiments on the real-worid data sets from UCI and applications in face location show the correctness and efficiency of the proposed method.

关键词： spectral clustering affinity matrix eigengap orthogonal eigenvector face detection

作者: Waning Kong Changsihe Sun Sanqing Hu Jianhai Zhang

作者单位: College of Computer Science, Hangzhou Dianzi University, Hangzhou, 310018, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 841-845

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）