{"id":"W2162407796","doi":"10.1109/ismvl.2002.1011094","title":"Variable selection heuristics and optimum decision trees-an experimental study","year":2003,"lang":"en","type":"article","venue":"","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Heuristics; Computation; Variable (mathematics); Heuristic; Decision tree; Computer science; Tree (set theory); Selection (genetic algorithm); Algorithm; Mathematical optimization; Feature selection; Node (physics); Mathematics; Artificial intelligence; Combinatorics; Engineering","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":[0.00371908,0.0006990709,0.001025192,0.001092382,0.0007104818,0.0009721807,0.001315104,0.0009228846,0.004582204],"category_scores_gemma":[0.02352542,0.0004561496,0.0006252528,0.002371082,0.000869449,0.001600525,0.0007281902,0.001754444,0.0006985342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181439,"about_ca_system_score_gemma":0.0009836499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001707239,"about_ca_topic_score_gemma":0.001821404,"domain_scores_codex":[0.9963251,0.002051676,0.0002347209,0.0004022203,0.000712149,0.0002742138],"domain_scores_gemma":[0.9414057,0.05164814,0.001130398,0.003399063,0.001932266,0.0004844434],"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":[0.006249632,0.005028674,0.009296807,0.001412696,0.0002943647,0.0003246865,0.0008399207,0.4968156,0.01626228,0.03040078,0.0112247,0.4218499],"study_design_scores_gemma":[0.0008388503,0.003025914,0.003670029,0.0001093688,0.0001117921,0.0002392404,0.0004105787,0.9340973,0.0273419,0.022632,0.007465587,0.00005741463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8596258,0.004396861,0.1154737,0.0005512278,0.0001475479,0.0005395297,0.001704415,0.001257096,0.01630383],"genre_scores_gemma":[0.8442376,0.0009824556,0.1507018,0.0000899161,0.00005454373,0.0003449892,0.00118186,0.0002021882,0.002204765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004582204,"threshold_uncertainty_score":0.01966858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03466934197519551,"score_gpt":0.3348605145672471,"score_spread":0.3001911725920516,"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."}}