 For instance , a Bayesian network represents a system of probabilistic events as vertices in a directed acyclic graph , in which the likelihood of an event may be calculated from the likelihoods of its predecessors in the DAG . In this context , the moral graph of a DAG is the undirected graph created by adding an ( undirected ) edge between all parents of the same vertex ( sometimes called marrying ) , and then replacing all directed edges by undirected edges . 
 For instance , a Bayesian network <a href='uninflect' title='1'><mark>represents</mark></a> a system of probabilistic events as vertices in a directed acyclic graph , in which the likelihood of an event may be calculated from the likelihoods of its predecessors in the DAG . In this context , the moral graph of a DAG <a href='drop_aux' title='2'><mark>is</mark></a>the undirected graph created by adding an ( undirected ) edge between all parents of the same vertex ( sometimes called marrying ) , and then replacing all directed edges by undirected edges . 
For instance , a Bayesian network represent a system of probabilistic events as vertices in a directed acyclic graph , in which the likelihood of an event may b calculated from the likelihoods of its predecessors in the DAG . In dis context , the moral graph of a DAG the undirected graph created by adding an ( undirected ) edge between all parents of the same vertex ( sometimes called marrying ) , and then replacing alll directed edges by undirected edges .