{"id":"W2101821333","doi":"10.5430/air.v3n1p38","title":"A statistical approach for clustering in streaming data","year":2014,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Computer science; Data stream mining; Data stream clustering; Component (thermodynamics); Data mining; Context (archaeology); Data stream; Concept drift; Streaming data; Focus (optics); Unsupervised learning; Machine learning; CURE data clustering algorithm; Correlation clustering","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":[0.004345395,0.001357806,0.001481493,0.00549507,0.001226809,0.001868776,0.002822417,0.001546105,0.001654768],"category_scores_gemma":[0.009961274,0.0008538174,0.002415372,0.006247174,0.001901635,0.003003834,0.002044769,0.002760816,0.001166366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001869964,"about_ca_system_score_gemma":0.001927332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005562381,"about_ca_topic_score_gemma":0.004533329,"domain_scores_codex":[0.9962407,0.001035963,0.0003200429,0.0009177011,0.001325123,0.0001603718],"domain_scores_gemma":[0.9953822,0.001941367,0.0004469235,0.0007184242,0.001343208,0.0001678129],"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":[0.0001602056,0.0001461581,0.00507481,0.0006506529,0.0004800966,0.0002772887,0.0005899241,0.4210598,0.006334155,0.1962122,0.01009728,0.3589175],"study_design_scores_gemma":[0.00001103922,0.00006045524,0.0008607609,0.00003205296,0.00002961295,0.0001358436,0.00007551063,0.9143606,0.001468384,0.07485354,0.008066509,0.00004576197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008486232,0.0003114855,0.9981477,0.0001092733,0.00004285882,0.00004593951,0.00008030121,0.0002183329,0.0001954282],"genre_scores_gemma":[0.06980352,0.001606264,0.9244331,0.0002205798,0.0004522267,0.0004622279,0.0009381341,0.0002314957,0.001852514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005562381,"threshold_uncertainty_score":0.02298093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4264192062234075,"score_gpt":0.4872538406245796,"score_spread":0.06083463440117209,"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."}}