{"id":"W2090571851","doi":"10.1109/tsmcb.2011.2170067","title":"An Optimization of Allocation of Information Granularity in the Interpretation of Data Structures: Toward Granular Fuzzy Clustering","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":220,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Granularity; Cluster analysis; Granular computing; Partition (number theory); Representation (politics); Computer science; Data mining; Theoretical computer science; Mathematics; Mathematical optimization; Algorithm; Artificial intelligence; Rough set","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":[0.004212937,0.0007172044,0.00129047,0.001976228,0.0006421051,0.002224721,0.001061135,0.001201531,0.0004918742],"category_scores_gemma":[0.0165975,0.0006875028,0.0008064928,0.002349546,0.002040084,0.003013382,0.002503431,0.001174361,0.0001456231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001165189,"about_ca_system_score_gemma":0.00101177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001011234,"about_ca_topic_score_gemma":0.0008108809,"domain_scores_codex":[0.9968482,0.00136751,0.0002695191,0.000547283,0.000795569,0.0001718773],"domain_scores_gemma":[0.9951384,0.002926979,0.0005896536,0.0007307709,0.0004855671,0.0001286063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003825636,0.0001221447,0.002096064,0.0005534672,0.0001332227,0.0002181955,0.001683588,0.5067249,0.02732752,0.1660686,0.001474864,0.2932148],"study_design_scores_gemma":[0.00004215876,0.0001375365,0.0005871878,0.00007180631,0.00004748552,0.0001108917,0.0002652528,0.8531181,0.007693679,0.1355784,0.002307146,0.00004039082],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01928996,0.0002239076,0.9796525,0.0001788574,0.000007696918,0.00003773066,0.00001943334,0.00005824359,0.0005316055],"genre_scores_gemma":[0.2857483,0.0002848824,0.713271,0.00007483074,0.0000317385,0.0001296811,0.00006247818,0.0000552041,0.000341775],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004212937,"threshold_uncertainty_score":0.0222804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04545019419210344,"score_gpt":0.257397987094498,"score_spread":0.2119477929023945,"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."}}