{"id":"W1534746498","doi":"","title":"Adaptive selection of ensembles for imbalanced class distributions","year":2012,"lang":"en","type":"article","venue":"Espace ÉTS (ETS)","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Skew; Computer science; Artificial intelligence; Boolean function; Class (philosophy); Reliability (semiconductor); Selection (genetic algorithm); Machine learning; Receiver operating characteristic; Pattern recognition (psychology); Data mining; Algorithm","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":[0.002987646,0.0007363549,0.00117375,0.001447189,0.0005052104,0.001049777,0.001139023,0.00065401,0.0009589499],"category_scores_gemma":[0.01130172,0.0003633619,0.000435756,0.0009643965,0.0004560235,0.001271294,0.001365063,0.0007568648,0.0005931663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006247941,"about_ca_system_score_gemma":0.0005697618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001201333,"about_ca_topic_score_gemma":0.001720655,"domain_scores_codex":[0.9980385,0.0006629435,0.0001162818,0.0003981313,0.0006167255,0.0001675239],"domain_scores_gemma":[0.9947686,0.002569532,0.0005633697,0.0006990072,0.001188172,0.0002112051],"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":[0.0005936353,0.0002114769,0.01534478,0.00009175363,0.0002020688,0.0001692622,0.0003166171,0.196009,0.03531547,0.00376554,0.002625855,0.7453546],"study_design_scores_gemma":[0.00001449553,0.00007272782,0.002037674,0.000007799606,0.00002516423,0.00008573045,0.00003186079,0.9867159,0.008156549,0.002114509,0.0007236953,0.00001401572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1092106,0.0002650657,0.8875728,0.0001488027,0.00004763292,0.00008770548,0.00007119981,0.001258501,0.001337552],"genre_scores_gemma":[0.7994723,0.0001046106,0.198563,0.0001232057,0.00007090656,0.0001596305,0.0002236857,0.0001018342,0.001180861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002987646,"threshold_uncertainty_score":0.01580042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02421894912144981,"score_gpt":0.2813993209002014,"score_spread":0.2571803717787515,"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."}}