A Characterization of Bayesian Network Structures and its Application to Leaming

James I. G. Forbes
Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:203-210, 1997.

Abstract

We present an analysis of the minimal I-map relation between Bayesian network structures and dependency models. This includes a partial order characterisation of the structures, and the connection between the relation and the arc reversal operation. Two applications of this analysis are presented. The first is a simple condition for identifying equivalence between Bayesian network structures, and the second is an exact learning algorithm based on the partial order characterisation.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR1-forbes97a, title = {A Characterization of Bayesian Network Structures and its Application to Leaming}, author = {Forbes, James I. G.}, booktitle = {Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics}, pages = {203--210}, year = {1997}, editor = {Madigan, David and Smyth, Padhraic}, volume = {R1}, series = {Proceedings of Machine Learning Research}, month = {04--07 Jan}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/r1/forbes97a/forbes97a.pdf}, url = {https://proceedings.mlr.press/r1/forbes97a.html}, abstract = {We present an analysis of the minimal I-map relation between Bayesian network structures and dependency models. This includes a partial order characterisation of the structures, and the connection between the relation and the arc reversal operation. Two applications of this analysis are presented. The first is a simple condition for identifying equivalence between Bayesian network structures, and the second is an exact learning algorithm based on the partial order characterisation.}, note = {Reissued by PMLR on 30 March 2021.} }
Endnote
%0 Conference Paper %T A Characterization of Bayesian Network Structures and its Application to Leaming %A James I. G. Forbes %B Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics %C Proceedings of Machine Learning Research %D 1997 %E David Madigan %E Padhraic Smyth %F pmlr-vR1-forbes97a %I PMLR %P 203--210 %U https://proceedings.mlr.press/r1/forbes97a.html %V R1 %X We present an analysis of the minimal I-map relation between Bayesian network structures and dependency models. This includes a partial order characterisation of the structures, and the connection between the relation and the arc reversal operation. Two applications of this analysis are presented. The first is a simple condition for identifying equivalence between Bayesian network structures, and the second is an exact learning algorithm based on the partial order characterisation. %Z Reissued by PMLR on 30 March 2021.
APA
Forbes, J.I.G.. (1997). A Characterization of Bayesian Network Structures and its Application to Leaming. Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, in Proceedings of Machine Learning Research R1:203-210 Available from https://proceedings.mlr.press/r1/forbes97a.html. Reissued by PMLR on 30 March 2021.

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