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On divergence and probability of error in pattern recognition

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1 Author(s)
Babu, C.Chitti ; University of California, Irvine, Calif.

An upperbound on the probability of error in classifying a pattern using Bayesian decision criterion is obtained in terms of its divergence and it is shown that the maximization of the divergence of the pattern minimizes this upperbound. Furthermore, a relationship between the divergence of a pattern and its nearest neighbor classification risk is presented.

Published in:

Proceedings of the IEEE  (Volume:61 ,  Issue: 6 )