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<p><b>Abstract</b>—This paper presents new upper and lower bounds on the minimum probability of error of Bayesian decision systems for the two-class problem. These bounds can be made arbitrarily close to the exact minimum probability of error, making them tighter than any previously known bounds.</p>
Bayesian decision, probability of error, statistical pattern recognition.
Hadar Avi-Itzhak, Thanh Diep, "Arbitrarily Tight Upper and Lower Bounds on the Bayesian Probability of Error", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 18, no. , pp. 89-91, January 1996, doi:10.1109/34.476017
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