{"id":"W2347824845","doi":"","title":"Parameters Optimization of Support Vector Machine based on Improved Genetic Algorithm","year":2010,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Computer science; Generalization; Genetic algorithm; Artificial intelligence; Machine learning; Algorithm; Ranking SVM; Pattern recognition (psychology); Data mining; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003629963,0.0001657955,0.0001511957,0.000102262,0.00007300251,0.00002177817,0.0002332406,0.00007765112,0.00006121321],"category_scores_gemma":[4.505145e-7,0.0001744875,0.00006837534,0.0002703142,0.0000494296,0.00004444083,0.00002154932,0.0001944884,0.00002934554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002124532,"about_ca_system_score_gemma":0.00001935271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007550374,"about_ca_topic_score_gemma":0.000002963273,"domain_scores_codex":[0.9992128,0.000005179935,0.0002777331,0.0002416627,0.00008072116,0.0001818722],"domain_scores_gemma":[0.9993339,0.00004429996,0.00006004654,0.0004140873,0.00006370224,0.0000840208],"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":[0.000001165156,0.0001045186,0.00001831589,0.00002015568,0.00001381088,1.443725e-7,0.00001787968,0.6644374,0.03605929,0.000148803,0.0001875411,0.2989909],"study_design_scores_gemma":[0.0002609467,0.00002772601,0.0003899704,0.000003467595,0.00001387084,0.000003438096,0.00000176198,0.9477531,0.01963765,0.00009948391,0.03163693,0.0001716157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009368947,0.00001424471,0.9976245,0.00007001797,0.00004186297,0.0006693669,0.0001534548,0.000245352,0.0002442924],"genre_scores_gemma":[0.04510865,0.000008669986,0.9537944,0.0001008593,0.000092196,0.0006414744,0.0001873341,0.00004422649,0.00002225802],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2988193,"threshold_uncertainty_score":0.7115392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003321803573914713,"score_gpt":0.2002190275090983,"score_spread":0.1968972239351836,"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."}}