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arxiv: 1301.7366 · v1 · pith:7RX5G63Onew · submitted 2013-01-30 · 💻 cs.AI

Marginalizing in Undirected Graph and Hypergraph Models

classification 💻 cs.AI
keywords graphhypergraphundirectedgivenmodelsaccordingallowanalysis
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Given an undirected graph G or hypergraph X model for a given set of variables V, we introduce two marginalization operators for obtaining the undirected graph GA or hypergraph HA associated with a given subset A c V such that the marginal distribution of A factorizes according to GA or HA, respectively. Finally, we illustrate the method by its application to some practical examples. With them we show that hypergraph models allow defining a finer factorization or performing a more precise conditional independence analysis than undirected graph models.

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