Algebraic Bayesian Networks: Naïve Frequentist Approach to Local Machine Learning Based on Imperfect Information from Social Media and Expert Estimates-Reference-Cited by-同舟云学术

Algebraic Bayesian Networks: Naïve Frequentist Approach to Local Machine Learning Based on Imperfect Information from Social Media and Expert Estimates

Published:2019 Issue: Volume: Page:234-244
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
Short-container-title:

Author:

Kharitonov Nikita A.^ORCID,Maximov Anatoly G.^ORCID,Tulupyev Alexander L.^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-30763-9_20

Reference26 articles.

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3. Azar, A., Dolatabad, K.M.: A method for modelling operational risk with fuzzy cognitive maps and Bayesian belief networks. Expert Syst. Appl. 115, 607–617 (2019)

4. Baggenstoss, P.M.: On the duality between belief networks and feed-forward neural networks. IEEE Trans. Neural Networks Learn. Syst. 30(1), 190–200 (2019)

5. Filchenkov, A.A., Tulupyev, A.L.: Coincidence of the sets of minimal and irreducible join graphs over primary structure of algebraic Bayesian networks. Vestnik St. Petersburg Univ. Math. 45(2), 106–113 (2012)

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