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Trudy SPIIRAN, 2010, Issue 14, Pages 132–149
(Mi trspy400)
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This article is cited in 9 scientific papers (total in 9 papers)
Join graph edges in context of algebraic Bayesian network minimal join graph cliques comparative analysis
A. A. Fil'chenkovab, A. L. Tulupyevab, A. V. Sirotkina a St. Petersburg Institute for Informatics and Automation of RAS
b St. Petersburg State University, Department of Mathematics and Mechanics
Abstract:
Algebraic Bayesian networks (ABN) are probabilistic-logic graphic models of knowledge systems with uncertainty and gives an advantage to deal with interval probability estimates. Secondary structure usually represented as an join graph is essential for ABN work. The article analyses edges of various minimal join graph cliques to specify different clique types. In particular, it is proven that vertex set of the class of cliques that are basic for minimal join graph set synthesis equals to set ofend of specifiededges, weight of those equals to the clique weight.
Keywords:
algebraic Bayesian networks, secondary structure, machine learning, probabilistic graphical knowledge models.
Received: 21.12.2010
Citation:
A. A. Fil'chenkov, A. L. Tulupyev, A. V. Sirotkin, “Join graph edges in context of algebraic Bayesian network minimal join graph cliques comparative analysis”, Tr. SPIIRAN, 14 (2010), 132–149
Linking options:
https://www.mathnet.ru/eng/trspy400 https://www.mathnet.ru/eng/trspy/v14/p132
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