{"id":"W1943768448","doi":"10.48550/arxiv.1301.6684","title":"Comparing Bayesian Network Classifiers","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Machine learning; Naive Bayes classifier; Artificial intelligence; Bayesian network; Conditional independence; Computer science; Bayesian programming; Bayes' theorem; Bayesian probability; Decision tree; Support vector machine; Bayes factor","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03537067,0.002411658,0.002471319,0.00929264,0.001716817,0.004837963,0.003604047,0.004079079,0.005692445],"category_scores_gemma":[0.144499,0.0006060093,0.001530765,0.004910995,0.00142983,0.01022707,0.002974078,0.003962952,0.002317263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004661123,"about_ca_system_score_gemma":0.002454776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00595261,"about_ca_topic_score_gemma":0.006250022,"domain_scores_codex":[0.9740321,0.01279788,0.001337919,0.003545437,0.007598244,0.0006885037],"domain_scores_gemma":[0.8946072,0.08958706,0.00267421,0.004228018,0.007799852,0.001103581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001798296,0.0006209689,0.02784724,0.0008924718,0.001054976,0.0001339908,0.0003403882,0.3793346,0.0007817115,0.0752003,0.01788535,0.4941097],"study_design_scores_gemma":[0.0001176161,0.0002145748,0.002615785,0.0002092493,0.000159906,0.0001385152,0.0001553572,0.8966744,0.001197308,0.09237746,0.00608637,0.00005333183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1076917,0.01026106,0.8490688,0.003487756,0.0009822514,0.0008101418,0.002038486,0.001538426,0.0241214],"genre_scores_gemma":[0.5996757,0.003824162,0.3845762,0.001175689,0.0007153611,0.0008711604,0.005301329,0.0003641227,0.003496334],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03537067,"threshold_uncertainty_score":0.1870602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1256933795164956,"score_gpt":0.1948135022175002,"score_spread":0.06912012270100468,"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."}}