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Bayesian Network post structure
Bumjun Kim edited this page Jan 4, 2017
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Bayesian Networks(BN) build on the same intuitions as the naive Bayes model by exploiting conditional independence properties of the distribution in order to allow a compact and natural representation. They allow us the flexibility to tailor our representation of the distribution to the independence properties that appear reasonable in the current setting. The core of the Bayesian network representation is a directed acyclic graph(DAG), whose nodes are the random variables in our domain and whose edges correspond, intuitively, to direct influence of one node on another.
This graph can be viewed in two very different ways