A probabilistic graphical model is a graph where :
- Nodes represent random variable.
- Edges (also called links or arcs) represents conditional dependence between these variables. Based on the edges, we distinguish :
- Undirected graphical models : Markov Random Fields (MRFs, or also called Markov networks)
- Directed graphical models or Bayesian Networks