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Some Upper Bounds on Error Probability for Multiclass Pattern Recognition

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1 Author(s)

An upper bound on the probability of error for the general pattern recognition problem is obtained as a functional of the pairwise Kolmogorov variational distances. Evaluation of the bound requires knowledge of a priori probabilities and of the class-conditional probability density functions. A tighter bound is obtained for the case of equal a priori probabilities, and a further bound is obtained that is independent of the a priori probabilities.

Published in:

IEEE Transactions on Computers  (Volume:C-20 ,  Issue: 8 )