Bayesian networks

One iteration CHC algorithm for learning Bayesian networks: an effective and efficient algorithm for high dimensional problems

It is well known that learning Bayesian networks from data is an NP-hard problem. For this reason, usually metaheuristics or approximate algorithms have been used to provide a good solution. In particular, the family of hill climbing algorithms has a …

Learning Bayesian networks by hill climbing: efficient methods based on progressive restriction of the neighborhood

Learning Bayesian networks is known to be an NP-hard problem and that is the reason why the application of a heuristic search has proven advantageous in many domains. This learning approach is computationally efficient and, even though it does not …