{"id":"W7133373697","doi":"","title":"Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification","year":2022,"lang":"en","type":"article","venue":"CityU Scholars","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Statistical learning theory; Support vector machine; Rate of convergence; Reproducing kernel Hilbert space; Statistical learning; Kernel (algebra); Convergence (economics); Linear inequality","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":[0.02928981,0.001831706,0.001855932,0.002868239,0.0009853434,0.003061051,0.003236363,0.002640259,0.003011275],"category_scores_gemma":[0.1273703,0.0008922049,0.001652821,0.001755156,0.004806604,0.008932111,0.004377186,0.005661691,0.0009451494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002995486,"about_ca_system_score_gemma":0.001633818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001230359,"about_ca_topic_score_gemma":0.0006353181,"domain_scores_codex":[0.9930955,0.003774782,0.0003326105,0.0008533229,0.001535462,0.0004083395],"domain_scores_gemma":[0.9023812,0.08090021,0.004101558,0.004582558,0.006613992,0.001420557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001978721,0.00007061413,0.00270771,0.0004346,0.0001227138,0.0001854219,0.0004030537,0.1665349,0.002105943,0.7924603,0.002094862,0.03268202],"study_design_scores_gemma":[0.00001174838,0.00008712454,0.0007497019,0.0001119019,0.00002582258,0.0001057563,0.00005457368,0.7853862,0.001319238,0.2106247,0.001483146,0.00004009806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02112569,0.002873,0.9702983,0.001613917,0.0001423574,0.00009811216,0.0001373444,0.0002092834,0.003502039],"genre_scores_gemma":[0.624135,0.007234826,0.3495303,0.001361848,0.001231899,0.001322989,0.001213018,0.001016191,0.01295396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02928981,"threshold_uncertainty_score":0.1549012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.230558225503552,"score_gpt":0.4320637594767343,"score_spread":0.2015055339731822,"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."}}