{"id":"W2055498865","doi":"10.1109/his.2013.6920500","title":"Measure optimized cost-sensitive neural network ensemble for multiclass imbalance data learning","year":2013,"lang":"en","type":"article","venue":"","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence; Ensemble learning; Machine learning; Subspace topology; Artificial neural network; Multiclass classification; Evolutionary algorithm; Focus (optics); Data mining; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007039155,0.0002149173,0.0002799093,0.00005300027,0.0002594526,0.0004030172,0.002055907,0.0001014826,0.00001266598],"category_scores_gemma":[0.0004679399,0.0001914326,0.00005276561,0.0003210185,0.00006447159,0.001903261,0.0008185219,0.0002502123,0.00009507974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005948306,"about_ca_system_score_gemma":0.0000603088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006629387,"about_ca_topic_score_gemma":0.00001316647,"domain_scores_codex":[0.9978184,0.0001694655,0.0003391997,0.0008204523,0.0002823644,0.0005700982],"domain_scores_gemma":[0.9968694,0.000512561,0.0001987347,0.001850512,0.0004390161,0.0001297967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001052002,0.00019334,0.001373542,0.00005106272,0.0001289798,0.0000109509,0.0004502,0.01666814,0.03576498,0.0505422,0.4565167,0.4381947],"study_design_scores_gemma":[0.0006227596,0.0000487447,0.001190717,0.00001750995,0.000006611783,0.00001003751,0.00003405748,0.9796913,0.005667827,0.0006266757,0.01181679,0.0002669383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002681043,0.00003985614,0.9926007,0.002463596,0.000249932,0.001440038,0.00002019484,0.001095393,0.001822168],"genre_scores_gemma":[0.2977803,0.00001556814,0.6996882,0.0008501408,0.0001261233,0.0002826331,0.000192189,0.0000208456,0.001043999],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9630232,"threshold_uncertainty_score":0.7806393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05602744217747754,"score_gpt":0.292739711454586,"score_spread":0.2367122692771085,"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."}}