DocumentCode :
918886
Title :
Strong consistency of an estimate of the asymptotic error probability of the nearest neighbor rule (Corresp.)
Author :
Wolverton, Charles T.
Volume :
19
Issue :
1
fYear :
1973
fDate :
1/1/1973 12:00:00 AM
Firstpage :
119
Lastpage :
120
Abstract :
Let 
be the asymptotic error probability of the nearest neighbor rule (NNR). A particular estimate of from 
-classified samples, known to converge to in probability as increases to infinity, is shown to actually converge with probability 1 to whenever the NNR itself converges with probability 1.
be the asymptotic error probability of the nearest neighbor rule (NNR). A particular estimate of from -classified samples, known to converge to in probability as increases to infinity, is shown to actually converge with probability 1 to whenever the NNR itself converges with probability 1.Keywords :
Estimation; Pattern classification; Error probability; H infinity control; Lagrangian functions; Layout; Maximum likelihood estimation; Nearest neighbor searches; Nonlinear equations; Nonlinear optics; Optical sensors; Relaxation methods;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1973.1054947
Filename :
1054947
Link To Document :
