Figure 1. The graphical vocabulary of the DDGraph.
The vocabulary consists of five types of nodes and two types of edges. For the edges, directed edges ending with dots indicate conditional independences between Xk and the target variable T given Xi. Undirected edges indicate dependencies, which involve T in different ways, and for conditional independencies between Xi and Xj given T. Consider a case of non-faithful distribution where T is an XOR function of X1 and X2 with carefully set parameters so that from data it looks like X1 and X2 are marginally independent of T. In this case, X1 and X2 would be conditionally dependent when conditioning on each other. This distribution would be represented as two dotted nodes with a dotted line between them, but disconnected from T. This kind of graph signals a non-faithful distribution where the neighbourhood and Markov blanket are not defined by transversing undirected edges from T.