Naive Bayes and Bayesian networks are both probabilistic models but Bayesian networks can represent conditional dependencies between variables while Naive Bayes assumes independence. To develop a Bayesian network model you identify variables, determine dependencies between variables, quantify these dependencies with conditional probabilities, and construct a directed acyclic graph representing the dependencies. Students are asked to post a 100-300 word response to the discussion question by Wednesday and engage with two other classmates' posts.

1. Discussion (Chapter 5): What is the relationship between Naïve
Bayes and Bayesian networks? What is the process of
developing a Bayesian networks model?
Note: The first post should be made by Wednesday 11:59 p.m.,
EST. I am looking for active engagement in the discussion.
Please engage early and often.
Your response should be 100-300 words. Respond to two
postings provided by your classmates.