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Fast kernel classifier construction using orthogonal forward selection to minimise leave-one-out misclassification rate

Hong, X., Chen, S. and Harris, C. J. (2006) Fast kernel classifier construction using orthogonal forward selection to minimise leave-one-out misclassification rate. Lecture Notes in Computer Science, 4113. pp. 106-114. ISSN 0302-9743 9783540372714

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To link to this item DOI: 10.1007/11816157_11

Abstract/Summary

We propose a simple yet computationally efficient construction algorithm for two-class kernel classifiers. In order to optimise classifier's generalisation capability, an orthogonal forward selection procedure is used to select kernels one by one by minimising the leave-one-out (LOO) misclassification rate directly. It is shown that the computation of the LOO misclassification rate is very efficient owing to orthogonalisation. Examples are used to demonstrate that the proposed algorithm is a viable alternative to construct sparse two-class kernel classifiers in terms of performance and computational efficiency.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:15273
Uncontrolled Keywords:IDENTIFICATION, REGRESSION
Additional Information:Proceedings Paper International Conference on Intelligent Computing (ICIC) AUG 16-19, 2006 Kunming, PEOPLES R CHINA

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