Learning Bayesian networks from big data with greedy search: computational complexity and efficient implementation

Learning the structure of Bayesian networks from data is known to be a computationally challenging, NP-hard problem. The literature has long investigated how to perform structure learning from data containing large numbers of variables, following a general interest in high-dimensional applications (...

Ausführliche Beschreibung