Some Variations on the PC Algorithm.
Joaquín Abellán, Manuel Gómez‐Olmedo, Serafı́n Moral · 2006
This paper proposes some possible modifications on the PC basic learning algorithm and makes some experiments to study their behaviour. The variations are: to determine minimum size cut sets between two nodes to study the deletion of a link, to make statistical decisions taking into account a Bayesian score instead of a classical Chi-square test, to study the refinement of the learned network by a greedy optimization of a Bayesian score, and to solve link ambiguities taking into account a measure of their strength. It will be shown that some of these modifications can improve PC performance, depending of the objective of the learning task: discovering the causal structure or approximating the joint probability distribution for the problem variables. 1