DocumentCode
2985673
Title
A Coreset-Based Semi-supverised Clustering Using One-Class Support Vector Machines
Author
Lei Gu
Author_Institution
Guangxi Key Lab. of Wireless Wideband Commun. & Signal Process., Guilin, China
fYear
2012
fDate
7-9 Dec. 2012
Firstpage
52
Lastpage
55
Abstract
The traditional one-class support vector machines problem can be transformed into solving the minimum enclosing 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.
Keywords
data handling; pattern clustering; support vector machines; coreset based semisupverised clustering; data clustering methods; enclosing ball problem; one class support vector machines; Accuracy; Clustering algorithms; Clustering methods; Kernel; Signal processing algorithms; Support vector machines; coreset; kernel methods; one-class support vector machines; semi-supervised clsutering;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
Conference_Location
Liaoning
Print_ISBN
978-1-4673-4499-9
Type
conf
DOI
10.1109/ICCECT.2012.165
Filename
6413916
Link To Document