{"id":"W3023454035","doi":"10.1109/tvcg.2020.3030354","title":"Explainable Matrix - Visualization for Global and Local Interpretability of Random Forest Classification Ensembles","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Interpretability; Computer science; Visualization; Random forest; Machine learning; Scalability; Artificial intelligence; Data mining; Data visualization; Visual analytics; Focus (optics); Creative visualization; Data science","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":[0.00152404,0.001350184,0.0005742479,0.002538737,0.0005246659,0.002783828,0.0008402049,0.0009521554,0.0116345],"category_scores_gemma":[0.009737998,0.0003784434,0.00108194,0.001198164,0.0005500603,0.002888847,0.00226487,0.001675854,0.001462015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005541753,"about_ca_system_score_gemma":0.0006377706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002553357,"about_ca_topic_score_gemma":0.002845006,"domain_scores_codex":[0.9992692,0.0002961363,0.00005671368,0.0001157462,0.0001936044,0.00006860642],"domain_scores_gemma":[0.9971427,0.001501364,0.0002309629,0.0004395309,0.0005614618,0.0001239964],"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":[0.0008536311,0.0001593989,0.0058108,0.001074071,0.0002061725,0.001121254,0.004656294,0.1347,0.05761347,0.1869813,0.05726531,0.5495583],"study_design_scores_gemma":[0.00006892164,0.00007945704,0.001917582,0.0001774389,0.00004986702,0.0004134991,0.0004536038,0.8212922,0.01654894,0.1234853,0.03542303,0.0000901337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01441591,0.0004219338,0.9716198,0.0008086258,0.0001266815,0.00006949285,0.001131312,0.008424648,0.002981636],"genre_scores_gemma":[0.3013014,0.0008534417,0.6900644,0.0002885405,0.0001501612,0.0003015464,0.002101349,0.002078651,0.002860411],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0116345,"threshold_uncertainty_score":0.0389213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03673167126332117,"score_gpt":0.3144207998614237,"score_spread":0.2776891285981025,"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."}}