Bayesian approach, theory of empirical risk minimization. Comparative analysis

Authors:
I. V. Sergienko;A. M. Gupal;A. A. Vagis
Affiliations:
V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine
Venue:
Cybernetics and Systems Analysis
Year:
2008

Citing 4
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Abstract

Error estimates of empirical-risk minimization methods for an infinite number of decision rules are analyzed. Optimal deterministic estimates of the error of the Bayesian classification procedure for independent features are obtained based on averaging over a great number of training samples as a control. For the Boolean case, the Bayesian procedure is equivalent to a classification procedure based on a separating hyperplane.