Discussion (Chapter 5) What is the relationship between Naïve Bayes.docx

Naive Bayes and Bayesian networks are both probabilistic classifiers but differ in their assumptions of independence between predictor variables. Bayesian networks are more flexible as they can represent dependencies between variables through a directed acyclic graph structure. To develop a Bayesian network model, one identifies variables of interest, determines conditional dependencies between variables, quantifies these dependencies with probabilities, and represents them in a network diagram.