A Multiple Spheres Weighted Support Vector Clustering Algorithm

被引：0
|
作者：
Sun, Sheng [1 ]
机构：
[1] Huangshi Inst Technol, Sch Comp Sci, Huangshi, Peoples R China
来源：
3RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND COMPUTER SCIENCE (ITCS 2011), PROCEEDINGS | 2011年
关键词：
clustering; support vector clustering; kernel method; Machine Learning;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Support vector clustering originates from the concept of support vector machine. It is a robust and unsupervised method. This paper improves the traditional SVC algorithm and presents a multiple spheres weighted support vector clustering (MW-SVC) algorithm. The MW-SVC algorithm is suitable for the normal condition that the clustering results of training samples are several clusters. It is fully automatic adaptively, runs fast and has highly accuracy rate. The results of experiment demonstrate the effectiveness of the proposed MW-SVC algorithm.
引用
收藏
页码：218 / 221
页数：4
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