The condensed nearest neighbor rule using the concept of mutual nearest neighborhood (Corresp.)

Authors:
K. Gowda;G. Krishna
Affiliations:
-;-
Venue:
IEEE Transactions on Information Theory
Year:
2006

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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.