{"id":"W2154187212","doi":"10.1007/3-540-39205-x_17","title":"Comparison of Conventional and Rough K-Means Clustering","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Cluster analysis; Data mining; Computer science; Rough set; Web mining; Set (abstract data type); Representation (politics); Interval (graph theory); Information retrieval; Web service; Machine learning; Mathematics; World Wide Web; Combinatorics","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":[0.003893371,0.0005715818,0.001175112,0.002690212,0.0009045165,0.002622078,0.001759466,0.0009877217,0.003591107],"category_scores_gemma":[0.01330478,0.0002144704,0.0006394302,0.003432863,0.0005605339,0.002368663,0.0008696694,0.0003756871,0.0008757414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001341622,"about_ca_system_score_gemma":0.001301073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00621077,"about_ca_topic_score_gemma":0.01026642,"domain_scores_codex":[0.9963518,0.0009704661,0.0002303817,0.0002940833,0.002013089,0.0001401339],"domain_scores_gemma":[0.993256,0.003100082,0.0001880409,0.0006778389,0.002685868,0.00009216441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006708313,0.0003120549,0.006128971,0.00322382,0.0008037015,0.0001691514,0.0009693058,0.1339383,0.009013296,0.02960209,0.01805663,0.7910743],"study_design_scores_gemma":[0.0004599423,0.001179668,0.02416111,0.0003078478,0.0009166038,0.0005811449,0.002148825,0.8992023,0.01481975,0.02765893,0.02827612,0.0002878045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4363599,0.023284,0.5002102,0.001162245,0.001414636,0.0003539185,0.001835818,0.002903843,0.03247538],"genre_scores_gemma":[0.7422223,0.003715901,0.2451395,0.0001019516,0.0001565751,0.0001325239,0.001999073,0.0003815493,0.006150622],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00621077,"threshold_uncertainty_score":0.02059036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04711995937113412,"score_gpt":0.303523117866409,"score_spread":0.2564031584952748,"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."}}