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Trudy SPIIRAN, 2010, Issue 12, Pages 97–118
(Mi trspy373)
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This article is cited in 20 scientific papers (total in 20 papers)
Algebraic Bayesian networks secondary structure analysis features
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:
The goal of this work is to generalize structure analysis of minimal join graphs representing algebraic Bayesian network secondary structure on common join graphs representing the same structure. A term system spreading the existing one with common join graphs is designed. New join graph properties are researched. Two lemmas characterizing an homage (product of a minimal join graph compression) as a minimal curia (product of a join graph compression) are proven. Theorem on minimal join graph proof is simplified.
Keywords:
algebraic Bayesian networks, secondary structure, join graphs, automated learning, machine learning, structure synthesis.
Received: 06.12.2010 Accepted: 06.12.2010
Citation:
A. A. Fil'chenkov, A. L. Tulupyev, A. V. Sirotkin, “Algebraic Bayesian networks secondary structure analysis features”, Tr. SPIIRAN, 12 (2010), 97–118
Linking options:
https://www.mathnet.ru/eng/trspy373 https://www.mathnet.ru/eng/trspy/v12/p97
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