The Quality of Training Sample Estimates of the Bhattacharyya Coefficient
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise
Arbitrarily Tight Upper and Lower Bounds on the Bayesian Probability of Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
Confidence intervals for probabilistic network classifiers
Computational Statistics & Data Analysis
Empirical bounds on error differences when using naive bayes
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
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In this paper, we present a new upper bound on the minimum probability of error of Bayesian decision systems for statistical pattern recognition. This new bound is continuous everywhere and is shown to be tighter than several existing bounds such as the Bhattacharyya and the Bayesian bounds. Numerical results are also presented.