{"id":"W1983690667","doi":"10.1016/s0004-3702(02)00191-1","title":"Learning Bayesian networks from data: An information-theory based approach","year":2002,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":803,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Carnegie Mellon University; University of Washington","keywords":"Bayesian network; Computer science; Conditional independence; Machine learning; Artificial intelligence; Bayesian probability; Independence (probability theory); Variable-order Bayesian network; Data mining; Bayesian inference; Theoretical computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09874819574461036,"score_gpt":0.2791029661627809,"score_spread":0.1803547704181706,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}