Gowda, K and Krishna, G (1979) The condensed nearest neighbor rule using the concept of mutual nearest neighborhood (Corresp.). In: IEEE Transactions on Information Theory, 25 (4). pp. 488-490.
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Abstract
A two-stage iterative algorithm for selecting a subset of a training set of samples for use in a condensed nearest neighbor (CNN) decision rule is introduced. The proposed method uses the concept of mutual nearest neighborhood for selecting samples close to the decision line. The efficacy of the algorithm is brought out by means of an example.
Item Type: | Editorials/Short Communications |
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Publication: | IEEE Transactions on Information Theory |
Publisher: | IEEE |
Additional Information: | Copyright 1979 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Department/Centre: | Others |
Date Deposited: | 25 Sep 2010 06:57 |
Last Modified: | 25 Sep 2010 06:57 |
URI: | http://eprints.iisc.ac.in/id/eprint/32411 |
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