k-nearest-neighbor Bayes-risk estimation
- 1 May 1975
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Information Theory
- Vol. 21 (3) , 285-293
- https://doi.org/10.1109/tit.1975.1055373
Abstract
Nonparametric estimation of the Bayes riskR^\astusing ak-nearest-neighbor (k-NN) approach is investigated. Estimates of the conditional Bayes errorr(X)for use in an unclassified test sample approach to estimateR^\astare derived using maximum-likelihood estimation techniques. By using the volume information as well as the class representations of thek-NN's toX, the mean-squared error of the conditional Bayes error estimate is reduced significantly. Simulations are presented to indicate the performance of the estimates using unclassified testing samples.Keywords
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