{"id":"W3036447434","doi":"10.1142/s0218213020600040","title":"Selecting and Combining Classifiers Based on Centrality Measures","year":2020,"lang":"en","type":"article","venue":"International Journal of Artificial Intelligence Tools","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Centrality; Computer science; Classifier (UML); Artificial intelligence; Machine learning; Random subspace method; Cascading classifiers; Feature selection; Pattern recognition (psychology); Data mining; 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":[0.003137795,0.001619078,0.001880155,0.006577248,0.001275333,0.002079327,0.001014663,0.0009567172,0.001799853],"category_scores_gemma":[0.01170502,0.0003434005,0.001133338,0.002645589,0.0004815843,0.00213023,0.001162482,0.0008642677,0.001114095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008933605,"about_ca_system_score_gemma":0.001296688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003573143,"about_ca_topic_score_gemma":0.004209335,"domain_scores_codex":[0.9961644,0.0006711204,0.0002830742,0.0005950283,0.001898696,0.0003875684],"domain_scores_gemma":[0.9948171,0.001960769,0.0003379844,0.0003036865,0.002367473,0.0002130017],"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":[0.000600621,0.0003079294,0.02935731,0.000326074,0.0005091109,0.0004370528,0.0004338051,0.06110443,0.04018976,0.00534323,0.006538694,0.854852],"study_design_scores_gemma":[0.00006437351,0.0006429672,0.02000879,0.0001624894,0.001054072,0.0008227528,0.0007016609,0.9047033,0.04042045,0.01721314,0.01408559,0.0001204723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2087798,0.002532765,0.7756982,0.0005822431,0.0004271478,0.0005489924,0.0003895149,0.001202302,0.009839053],"genre_scores_gemma":[0.7764579,0.0008939664,0.2175129,0.0001315684,0.0004028926,0.0002645133,0.0007327005,0.0001502021,0.003453355],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006577248,"threshold_uncertainty_score":0.01659447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1424332155885543,"score_gpt":0.3272338505991412,"score_spread":0.1848006350105869,"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."}}