Bayesian network

The Bayesian network is a network probabilistic, graphical model that describes dependencies.

Application

Bayesian networks have applications in machine learning tasks that deal with dependent features.

An example is Part-of-speech, where words are grammatically classified in a string. This involves a complex network of dependencies between object, subject, verbs, nouns, etc. that can be modeled and optimized with a Bayesian network.

Properties

DAG

Bayesian networks are directed, acyclic graphs.

Each edge identifies a causal relation, usually temporal: something that happened in the future cannot cause something to happen in the past. As such, the graph is acyclic.