A Generalization of the k-NN Rule
- 1 January 1976
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics
- Vol. SMC-6 (2) , 121-126
- https://doi.org/10.1109/tsmc.1976.5409182
Abstract
A modification of the k-nearest neighbors (k-NN) rule is presented in which classification is made not according to the ``majority vote'' but rather an integer threshold k1 (k1-NN rule). It is shown that while k-NN approximates the minimum expected error rule, k1-NN approximates the minimum expected risk rule with a threshold t. The relationship between t and values of k and k1 is derived. Several practical methods of using k1-NN for minimum expected risk classification and for classification with a reject option are described and illustrated with examples.Keywords
This publication has 4 references indexed in Scilit:
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- The Nearest Neighbor Classification Rule with a Reject OptionIEEE Transactions on Systems Science and Cybernetics, 1970
- The condensed nearest neighbor rule (Corresp.)IEEE Transactions on Information Theory, 1968
- Nearest neighbor pattern classificationIEEE Transactions on Information Theory, 1967