Max-min hill-climbing (MMHC) is a hybrid method which first estimates the skeleton of a
DAG using an algorithm called Max-Min Parents and Children and then performs a greedy
hill-climbing search to orient the edges with respect to a Bayesian score. It is a popular approach used as standard benchmark and also well suited for high-
dimensional domains.