bnlearn - Library for Bayesian network learning and inference

Added functionality to compute sctructure scores when using parameter of structure learning. This can help to decide which scoring type may give a better fit ('bic', 'k2', 'bdeu'). The results scores are directly stored in the output. import bnlearn as bn # Load example dataset df = bn.import_example('sprinkler') edges = [('Cloudy', 'Sprinkler'), ('Cloudy', 'Rain'), ('Sprinkler', 'Wet_Grass'), ('Rain', 'Wet_Grass')] # Make the actual Bayesian DAG DAG = bn.make_DAG(edges) model = bn.parameter_learning.fit(DAG, df) model['structure_scores'] {'k2': -33962.61414408797, 'bds': -57992.919156623604, 'bic': -94337.69274492635, 'bdeu': -33670.95375881856}If you use this software, please cite it using these metadata