{"id":"W4400733833","doi":"10.1007/s11222-024-10467-9","title":"Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection","year":2024,"lang":"en","type":"article","venue":"Statistics and Computing","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Centre hospitalier de l'Université Laval","funders":"Horizon 2020; Agence Nationale de la Recherche","keywords":"Discriminative model; Mutual information; Cluster analysis; Feature selection; Pattern recognition (psychology); Artificial intelligence; Joint (building); Feature (linguistics); Mathematics; Selection (genetic algorithm); Computer science; Data mining; 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":[0.001282828,0.0008231276,0.001331273,0.001186515,0.0003645169,0.0008417608,0.002207177,0.0009799728,0.002235717],"category_scores_gemma":[0.005809281,0.0006157843,0.001162705,0.001735662,0.0009586657,0.00169224,0.002108929,0.001423022,0.0009610957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008316114,"about_ca_system_score_gemma":0.001040219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005311464,"about_ca_topic_score_gemma":0.009549071,"domain_scores_codex":[0.998843,0.0004080709,0.00005281341,0.0002253014,0.0003746377,0.0000961973],"domain_scores_gemma":[0.9982775,0.0008273241,0.0001416186,0.0003661551,0.0003186585,0.00006869113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002242204,0.00011781,0.0009530516,0.0001970542,0.0001418595,0.00009890948,0.0001646087,0.6605139,0.01802519,0.07402129,0.006431516,0.2391106],"study_design_scores_gemma":[0.000005009083,0.00002384768,0.0003196358,0.000004781031,0.000007729564,0.00003631749,0.000008341423,0.9820604,0.001106304,0.01551756,0.0008999648,0.00001013655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003380629,0.0001037353,0.9956806,0.00007224963,0.00001405169,0.00001515349,0.00008239686,0.0002340946,0.0004170669],"genre_scores_gemma":[0.3675449,0.000668222,0.6234395,0.0002472686,0.0002449999,0.0002475277,0.001930204,0.0005053759,0.005171931],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005311464,"threshold_uncertainty_score":0.01056111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01879413297371209,"score_gpt":0.2502835027515293,"score_spread":0.2314893697778173,"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."}}