Graphical model: Difference between revisions

Revision as of 23:22, 24 March 2005

Revision as of 18:15, 5 May 2005

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:P(''X_i'' | parents of ''X_i'') for ''i'' = 1,...,''n''.

In other words, the [[probability distribution|joint distribution]] factors into a product of conditional distributions. The graph structure indicates direct dependencies among random variables. Any two nodes that are not in a descendantparent/ancestorchild relationship are [[Conditional independence|conditionally independent]] given the values of their parents. This type of graphical model is known as a directed graphical model, Bayesian network, or belief network. There are also undirected graphical models, a.k.a. Markov networks, in which graph separation encodes conditional independencies.

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