Bayesian networks — A quick dive

What are Bayesian networks?​

Bayesian networks are a type of Probabilistic Graphical Model that can be used to build models from data and/or expert opinion.

They can be used for a wide range of tasks including diagnostics, reasoning, causal modeling, decision making under uncertainty, anomaly detection, automated insight and prediction.

Figure below shows these capabilities in terms of the four major analytics disciplines, Descriptive analytics, Diagnostic analytics, Predictive analytics and Prescriptive analytics, plus Causal AI.

They are also commonly referred to as Bayes nets, Belief networks, Causal networks and Causal models.

Graphical​

Bayesian networks can be depicted graphically as shown in Figure 2, which shows the well known Asia network. Although visualizing the structure of a Bayesian network is optional, it is a great way to understand a model.