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A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate

Hong, X., Chen, S. and Harris, C. J. (2008) A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate. International Journal of Systems Science, 39 (2). pp. 119-125. ISSN 0020-7721

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To link to this item DOI: 10.1080/00207720701727822

Abstract/Summary

We propose a simple and computationally efficient construction algorithm for two class linear-in-the-parameters classifiers. In order to optimize model generalization, a forward orthogonal selection (OFS) procedure is used for minimizing the leave-one-out (LOO) misclassification rate directly. An analytic formula and a set of forward recursive updating formula of the LOO misclassification rate are developed and applied in the proposed algorithm. Numerical examples are used to demonstrate that the proposed algorithm is an excellent alternative approach to construct sparse two class 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:15276
Uncontrolled Keywords:classification, cross validation, forward regression, regularization, system identification, CLASS SEPARABILITY MEASURE, LEAST-SQUARES, IDENTIFICATION, REGRESSION

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