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:P(''X<sub>i</sub>'' | parents of ''X<sub>i</sub>'') 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 descendant/ancestor 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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