Mastering Predictive Analytics with R

Bayesian networks

Bayesian networks are a type of graphical model that involves a directed acyclic graph structure. We often refer to the tail node of a directed edge in a graphical model as the parent and the head node as the child or descendant. In fact, we generalize this latter notion so that if there is a path from node A to node B in the model, node B is a descendant of node A. We can distinguish the special case of node A connected to node B by saying that the latter is a direct descendant.

The parent relationship and the descendant relationship are mutually exclusive in a Bayesian network because it has no cycles. Bayesian networks have the distinguishing property that given its parents, every node in the network is conditionally independent ...