Enhanced Kernel Estimation Technique For Pattern-Classification

Lam, K.P. and Horne, E. (1993) Enhanced Kernel Estimation Technique For Pattern-Classification. Electronics Letters, 29 (24). pp. 2130-2131. ISSN 0013-5194. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1049/el:19931424

Abstract

The Letter reports the application of a nonparametric density estimation technique, the generalised K-nearest-neighbour (K-NN) method, to a novel pattern classifier for binary images. In addition to offering an improved error rate performance over the fixed kernel method previously adopted, the method can be used to measure the inherent difficulty of a pattern classification problem because the nearest-neighbour error rate bounds the Bayes rate.

Item Type: Article
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing
Depositing User: M. Nasiriavanaki
Date Deposited: 25 Jul 2009 20:16
Last Modified: 28 Jul 2009 08:07
Resource URI: http://kar.kent.ac.uk/id/eprint/22173 (The current URI for this page, for reference purposes)
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