{"id":"W2159276570","doi":"10.5539/cis.v5n4p110","title":"Improved SOM-Based High-Dimensional Data Visualization Algorithm","year":2012,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Coordinate system; Viewpoints; Self-organizing map; Point (geometry); Visualization; Data mining; Set (abstract data type); Algorithm; Data set; Multidimensional data; Artificial intelligence; Artificial neural network; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005804349,0.00008705532,0.00007293578,0.0001435402,0.0003851905,0.0004692152,0.0009830761,0.00002470882,0.000004913861],"category_scores_gemma":[0.00001137928,0.00007255095,0.0000108247,0.0007863922,0.0001319311,0.01660445,0.0007458999,0.00005572422,0.00003209343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001738988,"about_ca_system_score_gemma":0.0000884382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008015015,"about_ca_topic_score_gemma":1.507749e-7,"domain_scores_codex":[0.9989849,0.00001399491,0.0002226032,0.000199134,0.0003171601,0.0002622271],"domain_scores_gemma":[0.9989432,0.00004038206,0.0001038862,0.0005899186,0.0001562529,0.0001664214],"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":[0.000001076287,0.00004205746,0.0001234706,0.000007261605,0.000001945466,7.343788e-8,0.000203811,0.0008749418,0.000337027,0.1080257,0.002591137,0.8877915],"study_design_scores_gemma":[0.0001638357,0.00002105769,0.004270879,0.000005117123,0.000001422217,0.0000066177,0.000001637432,0.9857698,0.0004422639,0.0001161861,0.009097866,0.0001033214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003528799,0.00002412305,0.9951319,0.0004425318,0.0005188163,0.0001317371,0.000008615131,0.0001008974,0.0001125949],"genre_scores_gemma":[0.5934162,0.000008311028,0.4025976,0.003661795,0.0002046262,0.000009546677,0.00009283455,0.000002583074,0.000006455277],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9848949,"threshold_uncertainty_score":0.9971498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02167802021937798,"score_gpt":0.2783615712266175,"score_spread":0.2566835510072395,"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."}}