{"id":"W2109701649","doi":"10.1109/icsmc.2004.1401295","title":"An information-theoretic measure to evaluate data partitions in multiple classifiers","year":2005,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Boosting (machine learning); Computer science; Classifier (UML); Data mining; Machine learning; Uncorrelated; Artificial intelligence; Random subspace method; Benchmark (surveying); Training set; Measure (data warehouse); Pattern recognition (psychology); Mathematics; Statistics","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":[0.01783953,0.002136782,0.002809575,0.01294097,0.001576771,0.004280017,0.001891158,0.002548565,0.001766578],"category_scores_gemma":[0.04848643,0.0004487703,0.001487765,0.005467768,0.002499029,0.007452657,0.003203723,0.002334676,0.0005948514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002211573,"about_ca_system_score_gemma":0.00107883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005711183,"about_ca_topic_score_gemma":0.0006506823,"domain_scores_codex":[0.9870602,0.003868724,0.001217507,0.0009963178,0.006455503,0.0004017699],"domain_scores_gemma":[0.9664669,0.02205165,0.002775641,0.003130619,0.00496367,0.0006115278],"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":[0.001080974,0.0005724953,0.0307502,0.001004696,0.001797311,0.000384626,0.0006796232,0.2578574,0.0174092,0.09263929,0.009047262,0.586777],"study_design_scores_gemma":[0.0001181933,0.001872384,0.0188457,0.0003815798,0.0006397632,0.001198599,0.0005249936,0.8165162,0.02125281,0.1275373,0.01081151,0.000300935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04094941,0.002631842,0.9490464,0.0004768594,0.0002534449,0.0003108575,0.0005441065,0.0005387183,0.005248386],"genre_scores_gemma":[0.5459804,0.001205777,0.4477603,0.0003957075,0.0006009115,0.0008423433,0.001471219,0.0002524485,0.001490872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01783953,"threshold_uncertainty_score":0.09434563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07174330820983159,"score_gpt":0.3092844785362228,"score_spread":0.2375411703263912,"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."}}