{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007344431,0.0008342349,0.0007599178,0.001338737,0.0007176624,0.001077911,0.001140491,0.001003884,0.004404209],"category_scores_gemma":[0.002834836,0.0004051613,0.0009237199,0.0007540646,0.0004723857,0.0009829758,0.0008345745,0.001127022,0.001515849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009484233,"about_ca_system_score_gemma":0.001188684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00533578,"about_ca_topic_score_gemma":0.005874975,"domain_scores_codex":[0.9994424,0.0001364215,0.00002889593,0.0001418482,0.0001730969,0.00007721352],"domain_scores_gemma":[0.9990638,0.0004364725,0.00006488767,0.0001607278,0.0002539312,0.00002024524],"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":[0.0001647662,0.0001992725,0.002306693,0.0001194112,0.00006502621,0.0002076949,0.0001023119,0.2359511,0.02748446,0.01362051,0.005244378,0.7145344],"study_design_scores_gemma":[0.00001355892,0.0000373696,0.0003084601,0.000009008779,0.00001166816,0.00004135136,0.00001862061,0.982995,0.007585295,0.007540787,0.001430164,0.000008635571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01990835,0.00008436605,0.9729385,0.0001161507,0.00003213211,0.00007907881,0.0001376178,0.004599629,0.002104117],"genre_scores_gemma":[0.2978701,0.0000682474,0.6973112,0.0001090855,0.00001956059,0.0002245538,0.0005199691,0.000515393,0.003361868],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00533578,"threshold_uncertainty_score":0.01473355,"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."}}