Hadoop2010: Exact Inference in Bayesian Networks

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Probabilistic inference is a way of obtaining values of unobservable variables out of incomplete data. One tool for inference and a way to represent knowledge is a "Bayesian Network," where nodes represent variables and edges represent probabilistic dependencies between variables. While a lot of research has been devoted to devising schemes to approximate the solution, Hadoop allows performing exact inference on the whole network.

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