{"id":"W2074743521","doi":"10.1016/j.ins.2007.06.022","title":"Fuzzy functions with support vector machines","year":2007,"lang":"en","type":"article","venue":"Information Sciences","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Support vector machine; Fuzzy classification; Fuzzy logic; Fuzzy set operations; Data mining; Defuzzification; Neuro-fuzzy; Fuzzy rule; Artificial intelligence; Computer science; Fuzzy number; Fuzzy clustering; Fuzzy set; Mathematics; Fuzzy associative matrix; Machine learning; Pattern recognition (psychology); Fuzzy control system","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":[0.001493499,0.0008208573,0.001341283,0.001025017,0.0003468189,0.001529362,0.000902727,0.00128435,0.002952819],"category_scores_gemma":[0.007786679,0.0003715209,0.0007002398,0.001563289,0.0006191818,0.00200661,0.00100641,0.001398872,0.001471645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002797409,"about_ca_system_score_gemma":0.0003304849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006758139,"about_ca_topic_score_gemma":0.0003044556,"domain_scores_codex":[0.9989364,0.000487646,0.00007922247,0.000121396,0.0003270666,0.00004824757],"domain_scores_gemma":[0.9984841,0.0009240743,0.00009795599,0.0001789059,0.0002826916,0.00003236431],"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":[0.0004248016,0.0001043545,0.000515363,0.0004944796,0.0001436215,0.0001580819,0.00009960672,0.2159578,0.003368049,0.09371303,0.004742226,0.6802787],"study_design_scores_gemma":[0.00001736167,0.00006774234,0.0001644798,0.00003306502,0.00002154668,0.0000602645,0.00001421031,0.9085233,0.002026728,0.08564788,0.003407993,0.00001549917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004634625,0.001218221,0.9919728,0.0001494155,0.0001451425,0.000025899,0.00004861118,0.000236789,0.001568448],"genre_scores_gemma":[0.482162,0.002132959,0.5079094,0.0001437604,0.0006558768,0.0002292584,0.0002403073,0.000101177,0.006425219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002952819,"threshold_uncertainty_score":0.009878159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323109757490318,"score_gpt":0.2363759735314293,"score_spread":0.2231448759565261,"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."}}