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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Imprimir: 1064-2315
ISSN En Línea: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v42.i11.60
pages 58-63

Bayesian Recognition Procedures on Networks

Alexandra A. Vagis
V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine, Kiev, Ukraine

SINOPSIS

The polynomial algorithms of determining Bayesian network structure are described as "tree" or "polytree". In the known Bayesian network structure consideration is given to Bayesian recognition procedures built on learning samples by estimations of transition probabilities.

REFERENCIAS

  1. Gupal A.M., Sergienko I.V., Optimal recognition procedures.

  2. Vapnik V.N., Chervonenkis A.Ya., Theory of images recognition.

  3. Pearl J., Probabilistic reasoning in intelligent systems: networks of plausible inference.

  4. Gupal A.M., Vagis A.A., Statistical estimation of the Markov pattern recognition procedure.

  5. Anderson T.W., Goodman L.A., Statistical inference about Markov chains.

  6. Sergienko I.V., Beletskiy B.A., Gupal A.M., Predicting torsion angles in amino acid protein sequences based on a Bayesian classification procedure on Markov chains.


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