{"paper":{"title":"Kutato: An Entropy-Driven System for Construction of Probabilistic Expert Systems from Databases","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Edward H. Herskovits, Gregory F. Cooper","submitted_at":"2013-03-27T13:55:08Z","abstract_excerpt":"Kutato is a system that takes as input a database of cases and produces a belief network that captures many of the dependence relations represented by those data.  This system incorporates a module for determining the entropy of a belief network and a module for constructing belief networks based on entropy calculations.  Kutato constructs an initial belief network in which all variables in the database are assumed to be marginally independent.  The entropy of this belief network is calculated, and that arc is added that minimizes the entropy of the resulting belief network.  Conditional proba"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1304.1088","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"}