{"paper":{"title":"Conditions Under Which Conditional Independence and Scoring Methods Lead to Identical Selection of Bayesian Network Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.AI","authors_text":"Robert G. Cowell","submitted_at":"2013-01-10T16:23:01Z","abstract_excerpt":"It is often stated in papers tackling  the task of inferring  Bayesian network structures from data that there are these two  distinct approaches: (i) Apply conditional independence  tests when testing for the presence or otherwise of edges; (ii)  Search the model space using a scoring metric.     Here I argue that for complete data and a given node ordering this  division is a myth, by showing that cross entropy methods for  checking conditional independence are mathematically identical to  methods based upon discriminating between models by their overall  goodness-of-fit  logarithmic scores."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.2262","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}