{"id":"W4384030641","doi":"10.5220/0012090400003555","title":"Automated Feature Engineering for AutoML Using Genetic Algorithms","year":2023,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Feature (linguistics); Feature engineering; Genetic algorithm; Algorithm; Artificial intelligence; Machine learning; Deep learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001567843,0.00007880747,0.00007239974,0.000125198,0.00008734551,0.0001285592,0.0003337032,0.00004885546,0.000003369886],"category_scores_gemma":[0.00007064464,0.00007096359,0.0000308487,0.0005473092,0.000004590005,0.000149266,0.00008879398,0.00006658838,0.00005395464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002053822,"about_ca_system_score_gemma":0.00002780114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001672804,"about_ca_topic_score_gemma":5.873843e-7,"domain_scores_codex":[0.9993415,0.00001284864,0.00009038532,0.0002437745,0.0001081634,0.0002032801],"domain_scores_gemma":[0.9995029,0.00006687207,0.00003031826,0.0003180785,0.00003412796,0.00004770263],"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":[0.000005338984,0.00006020925,0.00140116,0.0002354088,0.00007996848,0.00003234533,0.0008280216,0.4898658,0.04290571,0.04981516,0.08123614,0.3335347],"study_design_scores_gemma":[0.0001049526,0.00001328771,0.01556859,0.000006930518,0.000002689172,0.000007960548,0.000003984046,0.9701063,0.0002556279,0.00005784083,0.01377689,0.00009496238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004915159,0.00002212135,0.9890124,0.001012268,0.0002887368,0.0001173107,0.000004153677,0.004522481,0.0001054034],"genre_scores_gemma":[0.05260479,0.000003982655,0.9459579,0.00008578005,0.0000997723,0.00002033209,0.00004739342,0.00001516127,0.001164869],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4802405,"threshold_uncertainty_score":0.2893811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02553456693664376,"score_gpt":0.2909624500239157,"score_spread":0.2654278830872719,"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."}}