A decomposition algorithm for learning Bayesian networks based on scoring function

DOI10.1155/2012/974063zbMath1263.62046OpenAlexW2037165900WikidataQ58907039 ScholiaQ58907039MaRDI QIDQ1951225

Mingmin Zhu, San-Yang Liu

Publication date: 3 June 2013

Published in: Journal of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2012/974063

Mathematics Subject Classification ID

Bayesian inference (62F15) Applications of graph theory (05C90) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• BNT
• RAIcode

Cites Work

• The max-min hill-climbing Bayesian network structure learning algorithm
• A conditional independence algorithm for learning undirected graphical models
• A Bayesian method for the induction of probabilistic networks from data
• Adaptive probabilistic networks with hidden variables
• Learning Bayesian networks from data: An information-theory based approach
• Decomposition of structural learning about directed acyclic graphs
• Decomposition of search for \(v\)-structures in DAGs
• Simple Linear-Time Algorithms to Test Chordality of Graphs, Test Acyclicity of Hypergraphs, and Selectively Reduce Acyclic Hypergraphs
• A Bayesian Network Learning Algorithm Based on Independence Test and Ant Colony Optimization
• Algorithmic Aspects of Vertex Elimination on Graphs
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