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Efficiency of the Bayesian Recognition Procedure

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Cybernetics and Systems Analysis Aims and scope

Abstract

The upper bound of the error of the Bayesian procedure for solving classification and recognition problems is obtained, depending on the number of attributes and the training-sample size. It is proved that the Bayesian method is suboptimal.

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REFERENCES

  1. A. M. Gupal,S. V. Pashko, andI. V. Sergienko, “Efficiency of the Bayesian classification procedure,” Kibern. Sist. Anal., No. 4, 78–89 (1995).

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  3. F. Hausdorff, Theory of Sets [Russian translation], Gl. Red. Tekh.-Teor. Lit., Moscow-Leningrad (1937).

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Authors and Affiliations

  1. National Bank of Ukraine, Kiev, Ukraine

    G. A. Vagis

  2. Scientific and Training Center of Applied Information Sciences, National Academy of Sciences of Ukraine, Kiev, Ukraine

    A. M. Gupal

  3. Cybernetics Institute, National Academy of Sciences of Ukraine, Kiev, Ukraine

    I. V. Sergienko

Authors
  1. G. A. Vagis
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  2. A. M. Gupal
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  3. I. V. Sergienko
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Vagis, G.A., Gupal, A.M. & Sergienko, I.V. Efficiency of the Bayesian Recognition Procedure. Cybernetics and Systems Analysis 37, 53–57 (2001). https://doi.org/10.1023/A:1016663916262

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  • DOI: https://doi.org/10.1023/A:1016663916262

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