Preprocessing Data for Creating Bayesian Networks

In this lesson, we will explore the conversion of networks into Bayesian networks, where nodes represent random variables and edges represent conditional dependencies. We'll build a suitable database for training a Bayesian network and understanding the structure and relationships between nodes.

Let’s imagine this scenario: We are city planners for a small town with ten distinct ...