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Dirichlet Bayesian network scores and the maximum relative entropy principle

Abstract:

A classic approach for learning Bayesian networks from data is to identify a maximum a posteriori (MAP) network structure. In the case of discrete Bayesian networks, MAP networks are selected by maximising one of several possible Bayesian–Dirichlet (BD) scores; the most famous is the Bayesian–Dirichlet equivalent uniform (BDeu) score from Heckerman et al. (Mach Learn 20(3):197–243, 1995). The key properties of BDeu arise from its uniform prior over the parameters of each local distribution in...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1007/s41237-018-0048-x

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Statistics
Role:
Author
Publisher:
Springer Publisher's website
Journal:
Behaviormetrika Journal website
Publication date:
2018-04-07
Acceptance date:
2018-03-29
DOI:
EISSN:
1349-6964
ISSN:
0385-7417
Pubs id:
pubs:832093
URN:
uri:d9d19201-dc19-488e-b2d2-d99dfe7e17c0
UUID:
uuid:d9d19201-dc19-488e-b2d2-d99dfe7e17c0
Local pid:
pubs:832093

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