Bayesian Networks

Bayesian networks are probabilistic graphical models depicting the relations within a potentially large set of variables. Commonly, Bayesian networks show the conditional dependencies, information that cannot easily be derived from, for example, a correlation table. Thus, these networks are a versatile tool for exploring and studying relations in large data sets and are used in many branches of science.

Graphical Model

In its essence, Bayesian network models are graphical visualizations of variables and their relations, whereby the values of their relations depend on random variation. Just as in structural equation models and factor models, for example, these visualizations show each variable as an ellipse, called a node, and the relations are depicted by arrows, called edges or ties, between variables.

The graph satisfies the formal requirements of Bayesian ...

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