{"id":"W1409342234","doi":"10.1007/s11063-015-9466-x","title":"Model-Based Clustering Based on Variational Learning of Hierarchical Infinite Beta-Liouville Mixture Models","year":2015,"lang":"en","type":"article","venue":"Neural Processing Letters","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Huaqiao University","keywords":"Cluster analysis; Dirichlet distribution; Computer science; Categorization; Artificial intelligence; Bayes' theorem; BETA (programming language); Computational intelligence; Hierarchical clustering; Hierarchical Dirichlet process; Machine learning; Mathematics; Pattern recognition (psychology); Latent Dirichlet allocation; Topic model; Bayesian probability","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":[0.00365441,0.0008994965,0.002546267,0.00192279,0.001487134,0.002658358,0.005164525,0.002508641,0.00228525],"category_scores_gemma":[0.01099467,0.001563061,0.002263347,0.00188401,0.002012423,0.003010602,0.00294926,0.002743868,0.0008950833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002529651,"about_ca_system_score_gemma":0.002128907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01249717,"about_ca_topic_score_gemma":0.01341854,"domain_scores_codex":[0.998276,0.0008319088,0.00008463059,0.0003155896,0.0003499236,0.000141971],"domain_scores_gemma":[0.9959487,0.002520943,0.0002555029,0.0003999508,0.0006672274,0.0002076461],"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":[0.00008144386,0.00004665968,0.0005366245,0.0000667718,0.00008353411,0.00003588371,0.000153174,0.883657,0.001418626,0.08898943,0.001176961,0.02375383],"study_design_scores_gemma":[0.000002353011,0.000002865672,0.00003368718,0.000002535448,0.000002870853,0.000004618787,0.000003330146,0.9892485,0.0001021784,0.01048053,0.0001107093,0.000005846099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005892575,0.0001089991,0.9930957,0.00009147237,0.00001647802,0.00001649222,0.00002747358,0.0001370765,0.0006136287],"genre_scores_gemma":[0.4117981,0.0004283478,0.5804704,0.0002872743,0.0001010089,0.0003000502,0.0008239052,0.000582376,0.005208523],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01249717,"threshold_uncertainty_score":0.02484882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04569327713784346,"score_gpt":0.2748998902295614,"score_spread":0.2292066130917179,"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."}}