GENERATIONS IN BAYESIAN NETWORKS
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Abstract
This paper focuses on the study of some aspects of the theory of oriented graphs in Bayesian networks. In some papers on the theory of Bayesian networks, the concept of “Generation of vertices” denotes a certain set of vertices with many parents belonging to previous generations. Terminology for this concept, in our opinion, has not yet fully developed. The concept of “Generation” in some cases makes it easier to solve some problems in Bayesian networks and to build simpler algorithms.
In this paper we will consider the well-known example “Asia”, described in many articles and books, as well as in the technical documentation for various toolboxes. For the construction of this example, we have used evaluation versions of AgenaRisk.
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References
AgenaRisk 7.0 User Manual. 2016.
Bidyuk P., Terentyev A.: Construction and methods of learning of Bayesian Networks. Tavricheskiy vestnik informatiki i matematiki 2/2004, 139–154.
Getting Started with AgenaRisk. 2013.
http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/020217.pdf (available 15.05.2019).
http://www.agenarisk.com (available 15.05.2019).
http://www.businessdataanalytics.ru/download/BayesianNetworks.pdf (available 15.05.2019).
http://www.cs.technion.ac.il/~dang/books/Learning%20Bayesian%20Networks(Neapolitan,%20Richard).pdf (available 15.05.2019).
http://www.stat.yale.edu/~jtc5/BioinformaticsCourse2001/MurphyBayesNetIntro.pdf (available 15.05.2019).
https://pdfs.semanticscholar.org/7bc7/54bc548f32b9ac53df67e3171e8e4df66d15.pdf (available 15.05.2019).
Jensen F. V., Nielsen T. D.: Bayesian Networks and Decision Graphs. Springer, 2007. DOI: https://doi.org/10.1007/978-0-387-68282-2
Litvinenko N., Litvinenko A., Mamyrbayev O., Shayakhmetova A.: On the issue of classification of types of evidence in Bayesian networks. IPIC, Almaty 2018.
Litvinenko N., Litvinenko A., Mamyrbayev O., Shayakhmetova A.: Work with Bayesian Networks in BAYESIALAB. IPIC, Almaty 2018.
Murphy K. P.: Machine Learning A Probabilistic Perspective. MIT Press, 2012.
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