{"id":"W4397003973","doi":"10.1142/s0219691324500279","title":"Generalization bounds of incremental SVM","year":2024,"lang":"en","type":"article","venue":"International Journal of Wavelets Multiresolution and Information Processing","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Wuhan Institute of Technology","keywords":"Generalization; Support vector machine; Computer science; Artificial intelligence; Mathematics; Pattern recognition (psychology); Mathematical analysis","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":[0.008595017,0.001567604,0.001628123,0.001858648,0.001100819,0.001853948,0.002825623,0.001841048,0.003447367],"category_scores_gemma":[0.04872606,0.0005577562,0.001533478,0.001516444,0.002672456,0.006088347,0.003887339,0.006181036,0.0008435959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00290912,"about_ca_system_score_gemma":0.001657079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003784882,"about_ca_topic_score_gemma":0.001955873,"domain_scores_codex":[0.9962562,0.001027281,0.0002098825,0.000772887,0.001284026,0.0004496887],"domain_scores_gemma":[0.9722525,0.0186673,0.00135349,0.002302164,0.004733409,0.0006910933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004281534,0.0000966962,0.004005885,0.0006573159,0.0001902962,0.0003114601,0.0005792454,0.4547634,0.005662283,0.3599269,0.008985801,0.1643925],"study_design_scores_gemma":[0.000006378193,0.00005915391,0.0004806246,0.00005849994,0.00002693412,0.00008989759,0.00003303611,0.9228452,0.001085013,0.0736585,0.001634847,0.00002187167],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02329791,0.006012641,0.9613413,0.001685591,0.0002324189,0.00007970915,0.0002212404,0.0004143985,0.006714821],"genre_scores_gemma":[0.7467887,0.009258862,0.2290238,0.001767782,0.001179185,0.0005700758,0.001311257,0.0006508759,0.009449506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008595017,"threshold_uncertainty_score":0.04545534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0108570483814005,"score_gpt":0.2657120807266893,"score_spread":0.2548550323452888,"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."}}