{"id":"W2113747757","doi":"10.1109/icdm.2005.119","title":"Partial Ensemble Classifiers Selection for Better Ranking","year":2006,"lang":"en","type":"article","venue":"","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Ranking (information retrieval); Computer science; AdaBoost; Machine learning; Artificial intelligence; Ensemble learning; Task (project management); Selection (genetic algorithm); Data mining; Ranking SVM; Learning to rank; Pattern recognition (psychology); Support vector machine; Engineering","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":[0.004262588,0.001017579,0.002359751,0.001803568,0.0008809692,0.001580943,0.001235568,0.00116873,0.0035739],"category_scores_gemma":[0.009469535,0.000364846,0.0008522613,0.00208478,0.0004400704,0.002956748,0.0009292884,0.001379361,0.001933281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000500499,"about_ca_system_score_gemma":0.001109785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009360616,"about_ca_topic_score_gemma":0.002516889,"domain_scores_codex":[0.9971808,0.001070326,0.000146427,0.0003430289,0.001013167,0.0002462337],"domain_scores_gemma":[0.994603,0.001987216,0.0003090177,0.001189183,0.001748339,0.0001632595],"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":[0.0001766567,0.0002241086,0.004377883,0.0001471193,0.0002540147,0.00009589407,0.00008260227,0.1421154,0.01294622,0.01617409,0.01503066,0.8083753],"study_design_scores_gemma":[0.00002262782,0.0001268045,0.001415174,0.00001321397,0.00005693012,0.00007408162,0.00002688809,0.9726246,0.00707203,0.01346196,0.005084158,0.00002158128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04503515,0.00086716,0.9481602,0.000316628,0.0002299304,0.00009142084,0.0001839559,0.001266654,0.003848917],"genre_scores_gemma":[0.545027,0.0006295075,0.444586,0.0002843022,0.0005278417,0.0002455635,0.001191012,0.0002929054,0.007215904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004262588,"threshold_uncertainty_score":0.02254295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01879128591362798,"score_gpt":0.2566670148366264,"score_spread":0.2378757289229984,"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."}}