{"id":"W1509534053","doi":"10.7939/r36d5ph6n","title":"Explaining Naive Bayes Classifications","year":2003,"lang":"en","type":"article","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Naive Bayes classifier; Computer science; Machine learning; Classifier (UML); Artificial intelligence; Training set; Bayes' theorem; Bayes classifier; Data mining; Bayesian probability; Support vector machine","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":[0.008464952,0.001854389,0.001000292,0.003106041,0.001411114,0.005184039,0.003703728,0.003374593,0.0158708],"category_scores_gemma":[0.04919129,0.0009420908,0.001971982,0.002301539,0.002004713,0.007023914,0.002280674,0.003149379,0.00365729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001793168,"about_ca_system_score_gemma":0.00169664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004335251,"about_ca_topic_score_gemma":0.004976489,"domain_scores_codex":[0.9912282,0.003997677,0.0005709163,0.001063233,0.002741632,0.0003982524],"domain_scores_gemma":[0.9722468,0.02074122,0.00126446,0.002282423,0.003220979,0.0002439705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002513236,0.0001203322,0.006950925,0.0007526659,0.0001599551,0.0006668841,0.001811525,0.05460982,0.002197583,0.6127269,0.04050253,0.2792495],"study_design_scores_gemma":[0.0000578787,0.00002955149,0.0007119453,0.0002631499,0.0000683416,0.0003343292,0.0001796419,0.2988836,0.002065291,0.6658909,0.03145562,0.00005971443],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003804973,0.0003418718,0.9867529,0.002055655,0.0001287491,0.00009637567,0.0007245163,0.002272132,0.003822897],"genre_scores_gemma":[0.1795266,0.001151231,0.8077329,0.00126382,0.0004279276,0.0004978041,0.002978919,0.0007608312,0.005659944],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0158708,"threshold_uncertainty_score":0.05309314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04605557111486784,"score_gpt":0.2702789424882792,"score_spread":0.2242233713734113,"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."}}