Title :
A Coreset-Based Semi-supverised Clustering Using One-Class Support Vector Machines
Author_Institution :
Guangxi Key Lab. of Wireless Wideband Commun. & Signal Process., Guilin, China
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;
Conference_Titel :
Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
Conference_Location :
Liaoning
Print_ISBN :
978-1-4673-4499-9
DOI :
10.1109/ICCECT.2012.165
