Bayesian networks, also known as belief networks or Bayes nets, are a type of graphical model that represent a set of variables and their conditional dependencies using a directed acyclic graph (DAG). In a Bayesian network: 1. **Nodes** represent random variables, which can be discrete or continuous. 2. **Directed Edges** indicate causal relationships or dependencies between the variables. An edge from node A to node B suggests that A has some influence on B.
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