{"id":"W2920973327","doi":"","title":"A Novel Cluster of Quarter Feature Selection Based on Symmetrical Uncertainty","year":2018,"lang":"en","type":"article","venue":"DergiPark (Istanbul University)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Feature selection; Data mining; Feature (linguistics); Computer science; Dimensionality reduction; Filter (signal processing); Curse of dimensionality; Pattern recognition (psychology); Artificial intelligence; Selection (genetic algorithm); Feature vector; Naive Bayes classifier; Machine learning; Support vector machine; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001442935,0.0007058941,0.001854587,0.002228523,0.0008700436,0.001062148,0.001350376,0.0006196629,0.001823796],"category_scores_gemma":[0.002417874,0.000300149,0.001234482,0.002552737,0.0004794734,0.001317898,0.0008932835,0.000543601,0.0004699142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005774078,"about_ca_system_score_gemma":0.001565294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00425071,"about_ca_topic_score_gemma":0.003398306,"domain_scores_codex":[0.9983069,0.0002903799,0.0001059727,0.0004091359,0.0006766361,0.0002110294],"domain_scores_gemma":[0.9988501,0.0002774948,0.00008350655,0.0001572374,0.000566172,0.00006553454],"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":[0.0004481058,0.0002396359,0.009614085,0.0001002902,0.0001651058,0.0001804562,0.0001760787,0.04767936,0.01973334,0.00422179,0.007692006,0.9097497],"study_design_scores_gemma":[0.00006515341,0.000346478,0.007000831,0.00001663402,0.00007654065,0.0003925826,0.0001513106,0.9670629,0.01305741,0.005871061,0.005907462,0.0000517136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05260134,0.0004889875,0.944025,0.0001869823,0.0000673683,0.0001356171,0.0002916867,0.001211215,0.0009917729],"genre_scores_gemma":[0.5802016,0.0003645903,0.412726,0.0002139022,0.0001497461,0.0003624482,0.001979148,0.0001544108,0.003848206],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00425071,"threshold_uncertainty_score":0.008451939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009705218735710692,"score_gpt":0.2040180812145723,"score_spread":0.1943128624788616,"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."}}