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Fixed size LS-SVM for multiclassification problems of large data sets  

Hwang, Hyung-Tae (Department of Statistics, Dankook University)
Publication Information
Journal of the Korean Data and Information Science Society / v.21, no.3, 2010 , pp. 561-567 More about this Journal
Abstract
Multiclassification is typically performed using voting scheme methods based on combining a set of binary classifications. In this paper we use multiclassification method with a hat matrix of least squares support vector machine (LS-SVM), which can be regarded as the revised one-against-all method. To tackle multiclass problems for large data, we use the $Nystr\ddot{o}m$ approximation and the quadratic Renyi entropy with estimation in the primal space such as used in xed size LS-SVM. For the selection of hyperparameters, generalized cross validation techniques are employed. Experimental results are then presented to indicate the performance of the proposed procedure.
Keywords
Fixed size least squares support vector machine; generalized cross validation; multiclass; $Nystr\ddot{o}m$ approximation; quadratic Renyi entropy;
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Times Cited By KSCI : 5  (Citation Analysis)
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