Asharaf, S and Shevade, SK and Murty, Narasimha M (2005) Rough support vector clustering. In: Pattern Recognition, 38 (10). pp. 1779-1783.
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In this paper a novel kernel-based soft clustering method is proposed. This method incorporates rough set theoretic ﬂavour in support vector clustering paradigm to achieve soft clustering. Empirical studies show that this method can find soft clusters having arbitrary shapes.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Pattern Recognition Society.|
|Keywords:||Rough sets;Soft clustering;Kernel function;Support vectors|
|Department/Centre:||Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)|
|Date Deposited:||03 Dec 2007|
|Last Modified:||19 Sep 2010 04:26|
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