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Learning Bayesian networks in Semi-deterministic systems

Luo, Wei 2006, Learning Bayesian networks in Semi-deterministic systems, in Canadian AI 2006 : Advances in artificial intelligence : 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Quebec City, Québec, Canada, June 7-9, 2006 : proceedings, Springer, Berlin, Germany, pp. 230-241, doi: 10.1007/11766247_20.

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Title Learning Bayesian networks in Semi-deterministic systems
Author(s) Luo, WeiORCID iD for Luo, Wei orcid.org/0000-0002-4711-7543
Conference name Canadian Society for Computational Studies of Intelligence. Conference (19th : 2006 : Quebec, Quebec)
Conference location Quebec City, Quebec
Conference dates 7-9 Jun. 2006
Title of proceedings Canadian AI 2006 : Advances in artificial intelligence : 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Quebec City, Québec, Canada, June 7-9, 2006 : proceedings
Editor(s) Lamontagne, Luc
Marchand, Mario
Publication date 2006
Conference series Canadian Society for Computational Studies of Intelligence Conference
Start page 230
End page 241
Total pages 12
Publisher Springer
Place of publication Berlin, Germany
Summary In current constraint-based (Pearl-style) systems for discovering Bayesian networks, inputs with deterministic relations are prohibited. This restricts the applicability of these systems. In this paper, we formalize a sufficient condition under which Bayesian networks can be recovered even with deterministic relations. The sufficient condition leads to an improvement to Pearl’s IC algorithm; other constraint-based algorithms can be similarly improved. The new algorithm, assuming the sufficient condition proposed, is able to recover Bayesian networks with deterministic relations, and moreover suffers no loss of performance when applied to nondeterministic Bayesian networks.
ISBN 9783540346289
3540346287
Language eng
DOI 10.1007/11766247_20
Field of Research 170203 Knowledge Representation and Machine Learning
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2006, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30052501

Document type: Conference Paper
Collection: Centre for Pattern Recognition and Data Analytics
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