A Self-Adaptive Spectral Clustering Algorithm

被引：3

作者：

Cai Xiaoyan ^{[1
]}

Dai Guanzhong ^{[1
]}

Yang Libin ^{[1
]}

Zhang Guoqing ^{[1
]}

机构：

[1] NW Polytech Univ, Sch Automat Control, Xian 710072, Peoples R China

来源：

PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 4 | 2008年

关键词：

Spectral Clustering; Number of the clusters; Self-adaptive;

D O I：

10.1109/CHICC.2008.4605517

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Most existing algorithms on spectral clustering are not able to determine the number of clusters. In this paper, we prove theoretically that the eigenvectors of the affinity matrix can be used directly to cluster the data points. And we-suggest exploiting the structure of the eigenvectors to infer automatically the number of clusters. As a result, a self-adaptive spectral clustering algorithm based on affinity matrix is proposed. The experimental results on the UCI data sets show that the algorithm is more effective than previous algorithms.

引用

页码：551 / 553

页数：3

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