{"id":"W2751237624","doi":"10.1007/978-3-540-88425-5_7","title":"A Note on Attribute Reduction in the Decision-Theoretic Rough Set Model","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Rough set; Reduction (mathematics); Attribute domain; Computer science; Probabilistic logic; Monotonic function; Set (abstract data type); Interpretation (philosophy); Dominance-based rough set approach; Decision table; Data mining; Decision rule; Artificial intelligence; Algorithm; Mathematics","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":[0.006512838,0.001122383,0.002637976,0.002378491,0.001287583,0.004846695,0.002798405,0.001800075,0.004079723],"category_scores_gemma":[0.01052725,0.001013782,0.004950517,0.004169397,0.004775481,0.008206712,0.003940925,0.008562317,0.00132668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002084372,"about_ca_system_score_gemma":0.001431737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002321057,"about_ca_topic_score_gemma":0.001546058,"domain_scores_codex":[0.994408,0.00249761,0.0003138955,0.0006080761,0.001968987,0.0002033896],"domain_scores_gemma":[0.9948678,0.003641831,0.0001506278,0.0008735232,0.000378873,0.00008730681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002521339,0.0000351536,0.00007840122,0.0001530572,0.00006453649,0.00007213043,0.000174383,0.01339789,0.0002870512,0.9547433,0.003813921,0.02715485],"study_design_scores_gemma":[0.000004430544,0.00001330993,0.00004083628,0.00002441824,0.00002003157,0.00003079208,0.00001522472,0.01419528,0.0001323172,0.9787562,0.006750799,0.00001636021],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003602169,0.009241346,0.9558485,0.00627124,0.001414875,0.00008595537,0.00022174,0.0001499433,0.02316432],"genre_scores_gemma":[0.2074193,0.01694961,0.7491367,0.002540802,0.004597865,0.0004126639,0.0005266345,0.0002912229,0.01812522],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006512838,"threshold_uncertainty_score":0.03444356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03217125286784099,"score_gpt":0.2674833912212478,"score_spread":0.2353121383534068,"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."}}