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The Nearest Neighbor and the Bayes Error Rates
February 1987 (vol. 9 no. 2)
pp. 254-262
George Loizou, Department of Computer Science, Birkbeck College, University of London, Malet Street, London WC1E 7HX, England.
Stephen J. Maybank, Marconi Command and Control Systems, Frimley, Surrey GU16 5PE, England; Department of Computer Science, Birkbeck College, University of London, Malet Street, London WC1E 7HX, Engla
The (k, l) nearest neighbor method of pattern classification is compared to the Bayes method. If the two acceptance rates are equal then the asymptotic error rates satisfy the inequalities Ek,l + 1 ¿ E*(¿) ¿ Ek,l dE*(¿), where d is a function of k, l, and the number of pattern classes, and ¿ is the reject threshold for the Bayes method. An explicit expression for d is given which is optimal in the sense that for some probability distributions Ek,l and dE* (¿) are equal.
Citation:
George Loizou, Stephen J. Maybank, "The Nearest Neighbor and the Bayes Error Rates," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 9, no. 2, pp. 254-262, Feb. 1987, doi:10.1109/TPAMI.1987.4767899
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