An efficient Bayesian network structure learning strategy

DOI10.1007/s00354-016-0007-6zbMath1442.68205OpenAlexW2560575251MaRDI QIDQ1670500

Joe Suzuki

Publication date: 5 September 2018

Published in: New Generation Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00354-016-0007-6

zbMATH Keywords

scoreupper boundBayesian network structure learningbranch and bound (B\&B)maximizing the posterior probabilityparent set

Mathematics Subject Classification ID

Bayesian inference (62F15) Learning and adaptive systems in artificial intelligence (68T05) Probabilistic graphical models (62H22)

Related Items

Bayesian network models for incomplete and dynamic data ⋮ Who learns better Bayesian network structures: accuracy and speed of structure learning algorithms ⋮ Learning Bayesian networks from incomplete data with the node-average likelihood ⋮ Learning Bayesian networks from big data with greedy search: computational complexity and efficient implementation

Uses Software

• TETRAD
• GOBNILP

Cites Work

• Modeling by shortest data description
• Causation, prediction, and search
• A Bayesian method for the induction of probabilistic networks from data
• Adaptive probabilistic networks with hidden variables
• The performance of universal encoding
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