Characterization of inclusion neighbourhood in terms of the essential graph

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Characterization of inclusion neighbourhood in terms of the essential graph

The question of efficient characterization of inclusion neighbourhood is crucial in some methods for learning (equivalence classes of) Bayesian networks. In this paper, neighbouring equivalence classes of a given equivalence class of Bayesian networks are characterized efficiently in terms of the respective essential graph. One can distinguish two kinds of inclusion neighbours: upper and lower ...

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The topic of the contribution is to characterize the inclusion neighbourhood of a given equivalence class of Bayesian networks in terms of the respective essential graph in such a way that it can be used eeciently in a method of local search for maximization of a quality criterion. One can distinguish two kinds of inclusion neighbours: upper and lower ones. A previous paper 15] gave a character...

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The problem of eecient characterization of inclusion neighbourhood is crucial for some methods of learning (equivalence classes of) Bayesian networks. In this paper, neighbouring equivalence classes of a given equivalence class of Bayesian networks are characterized eeciently by means of the respective essential graph. The characterization reveals hidded internal structure of the inclusion neig...

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ژورنال

عنوان ژورنال: International Journal of Approximate Reasoning

سال: 2005

ISSN: 0888-613X

DOI: 10.1016/j.ijar.2004.05.007