{"id":"W2103535650","doi":"10.1109/tsmcb.2005.863371","title":"Rough–Fuzzy Collaborative Clustering","year":2006,"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":258,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Cluster analysis; Data mining; Partition (number theory); Fuzzy clustering; Computer science; Fuzzy logic; Cluster (spacecraft); Measure (data warehouse); Consensus clustering; Artificial intelligence; Mathematics; CURE data clustering algorithm","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":[0.003557315,0.00106903,0.002034857,0.002961232,0.001423663,0.002521354,0.002694263,0.001660547,0.00229382],"category_scores_gemma":[0.008274814,0.0006184369,0.001767437,0.002452258,0.001263736,0.002321966,0.00212801,0.001118493,0.001530571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170529,"about_ca_system_score_gemma":0.001433626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002692254,"about_ca_topic_score_gemma":0.002588254,"domain_scores_codex":[0.9958833,0.00105412,0.00025058,0.0009771605,0.001653104,0.000181644],"domain_scores_gemma":[0.9970566,0.000846909,0.0002954747,0.0008373195,0.0008522019,0.0001114259],"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":[0.0001724433,0.0001760431,0.002082309,0.0006375775,0.0005730902,0.0003322026,0.0007358656,0.433554,0.00904761,0.1659304,0.007467256,0.3792912],"study_design_scores_gemma":[0.00002590566,0.00009207383,0.000798545,0.00004595767,0.00008640623,0.0002122942,0.0001242752,0.8930607,0.003816277,0.08774637,0.0139177,0.00007351638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004914925,0.0003424636,0.9918046,0.0001123429,0.00004390223,0.00009264297,0.00005357005,0.0001367745,0.002498782],"genre_scores_gemma":[0.2034631,0.0006794886,0.7901998,0.0001367289,0.0001612435,0.0002676287,0.0005539866,0.00006603693,0.0044721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003557315,"threshold_uncertainty_score":0.01881307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446450397479102,"score_gpt":0.2229931761474985,"score_spread":0.2085286721727075,"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."}}