Bayesian Networks

Abstract

Bayesian networks are probabilistic models based on direct acyclic graphs. These models enable a direct representation of causal relations between variables. Their structure is ideal for combining prior knowledge, which often comes in causal form, and observed data. This article gives a short description of the concepts of this important class of models that have become extremely popular in recent years.