{"id":"W2113439791","doi":"10.5539/cis.v4n3p88","title":"A Genetic K-means Clustering Algorithm Based on the Optimized Initial Centers","year":2011,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Cluster analysis; Cluster (spacecraft); Convergence (economics); Algorithm; Genetic algorithm; k-medoids; k-medians clustering; CURE data clustering algorithm; Correlation clustering; Artificial intelligence; Machine learning","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":[0.0008158673,0.001473566,0.001639262,0.001779395,0.001658067,0.001190712,0.002390823,0.001789281,0.001478267],"category_scores_gemma":[0.002490089,0.0007473806,0.001074746,0.002424834,0.001046358,0.001464697,0.001051252,0.001486833,0.001035665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00145309,"about_ca_system_score_gemma":0.002901457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01369583,"about_ca_topic_score_gemma":0.009586503,"domain_scores_codex":[0.9989618,0.0001939282,0.00004504824,0.0003413415,0.0003663886,0.00009147215],"domain_scores_gemma":[0.9993172,0.0001557422,0.00007279197,0.00007819254,0.0003432251,0.00003288629],"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":[0.0001476164,0.0001132499,0.002039005,0.000251148,0.000185905,0.0001398935,0.0003080851,0.5820819,0.01806258,0.01892113,0.008488504,0.3692611],"study_design_scores_gemma":[0.00004356218,0.00004614997,0.0005005308,0.000020008,0.00003926817,0.0001353442,0.00004677442,0.9812801,0.007490976,0.006046073,0.004295561,0.00005553668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006243119,0.0001677286,0.9912907,0.00007375911,0.00005453717,0.00008320226,0.0000405976,0.0008858165,0.00116053],"genre_scores_gemma":[0.07496224,0.0002192554,0.9217492,0.00006948914,0.00003523644,0.0003680669,0.0002566964,0.0001798448,0.002159978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01369583,"threshold_uncertainty_score":0.02723223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03516400012188189,"score_gpt":0.2771619605297209,"score_spread":0.241997960407839,"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."}}