Chain event graph map model selection
Thwaites, Peter, Freeman, Guy and Smith, J. Q., 1953- (2009) Chain event graph map model selection. In: 1st International Conference on Knowledge Engineering and Ontology Development, Funchal, Portugal, 06-08 Oct 2009 . Published in: KEOD 2009: proceedings of the international conference on knowledge engineering and ontology development pp. 392-395.Full text not available from this repository.
When looking for general structure from a finite discrete data set one can search over the class of Bayesian Networks (BNs). The class of Chain Event Graph (CEG) models is however much more expressive and is particularly suited to depicting hypotheses about how situations might unfold. Like the BN, the CEG admits conjugate learning on its conditional probability parameters using product Dirichlet priors. The Bayes Factors associated with different CEG models can therefore be calculated in an explicit closed form, which means that search for the maximum a posteriori (MAP) model in this class can be enacted by evaluating the score function of successive models and optimizing. Local search algorithms can be devised for the class of candidate models, but in this paper we concentrate on the process of scoring the members of this class.
|Item Type:||Conference Item (Paper)|
|Divisions:||Faculty of Science > Statistics|
|Journal or Publication Title:||KEOD 2009: proceedings of the international conference on knowledge engineering and ontology development|
|Page Range:||pp. 392-395|
|Conference Paper Type:||Paper|
|Title of Event:||1st International Conference on Knowledge Engineering and Ontology Development|
|Type of Event:||Conference|
|Location of Event:||Funchal, Portugal|
|Date(s) of Event:||06-08 Oct 2009|
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