A Coreset-based Semi-supverised Clustering Using One-class Support Vector Machines

被引：2
|
作者：
Gu, Lei [1 ,2 ]
机构：
[1] Guangxi Key Lab Wireless Wideband Commun & Signal, Guilin, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Sch Comp Sci & Tech, Nanjing, Peoples R China
来源：
2012 INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING AND COMMUNICATION TECHNOLOGY (ICCECT 2012) | 2012年
关键词：
coreset; kernel methods; one-class support vector machines; semi-supervised clsutering;
D O I：
10.1109/ICCECT.2012.165
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The traditional one-class support vector machines problem can be transformed into solving the minimum encloseing ball problem by the use of the corset. In this paper, the notion of the corset is applied to a semi-supervised clustering using one-class support vector machines. Experimental results show that this proposed algorithm not only can maintain the clustering performance, but also can decrease the running time of the clustering method.
引用
收藏
页码：52 / 55
页数：4
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