{"id":"W2378132571","doi":"","title":"One Method of Attribute Reduction Base on Rough Set Theory and Apply in Pattern Recognition","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rough set; Computer science; Reduction (mathematics); Pattern recognition (psychology); Base (topology); Set (abstract data type); Data mining; Attribute domain; Artificial intelligence; Set theory; Value (mathematics); Dominance-based rough set approach; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002116649,0.001027693,0.00173523,0.0040074,0.001129805,0.002035449,0.001273565,0.0009636634,0.003066771],"category_scores_gemma":[0.003442333,0.0005213788,0.002897645,0.003423806,0.001332458,0.002739253,0.001269401,0.002046503,0.001226613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007780571,"about_ca_system_score_gemma":0.001596956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001501375,"about_ca_topic_score_gemma":0.001133158,"domain_scores_codex":[0.996854,0.00081886,0.0002427698,0.00059386,0.00138047,0.0001100247],"domain_scores_gemma":[0.9990153,0.0003818956,0.00006687296,0.000195518,0.0003095405,0.00003081116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008833826,0.0001371502,0.001192646,0.001304867,0.0003957436,0.0002643445,0.0006033193,0.02496362,0.008011945,0.1855099,0.01281187,0.7647163],"study_design_scores_gemma":[0.0002800981,0.0005697029,0.004026077,0.0004661434,0.0006871031,0.003193699,0.0005484033,0.3003447,0.03194965,0.4920014,0.1652803,0.0006527497],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001648848,0.002033113,0.9913795,0.0003530837,0.0002287847,0.0001555458,0.0001050926,0.0004052246,0.003690814],"genre_scores_gemma":[0.08318217,0.004709612,0.9051812,0.000321865,0.000439122,0.0006134872,0.0005051804,0.0001655969,0.004881675],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0040074,"threshold_uncertainty_score":0.01119405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03190269789698538,"score_gpt":0.2814850795089896,"score_spread":0.2495823816120042,"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."}}