{"id":"W2100729317","doi":"10.4018/jdwm.2006070102","title":"A TOPSIS Data Mining Demonstration and Application to Credit Scoring","year":2006,"lang":"en","type":"article","venue":"International Journal of Data Warehousing and Mining","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"TOPSIS; Ideal solution; Computer science; Data mining; Similarity (geometry); Classifier (UML); Machine learning; Artificial intelligence; Operations research; Mathematics","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":[0.006968051,0.001282252,0.001062506,0.005011566,0.002046328,0.004034487,0.001217275,0.001022957,0.01047904],"category_scores_gemma":[0.01939591,0.0003612942,0.001225288,0.007745767,0.00124002,0.002379796,0.001935986,0.002054206,0.001735704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001905772,"about_ca_system_score_gemma":0.003265701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007706863,"about_ca_topic_score_gemma":0.008035202,"domain_scores_codex":[0.9945053,0.002502916,0.0003356605,0.0002965708,0.002249973,0.0001096561],"domain_scores_gemma":[0.9932529,0.003469434,0.0004162409,0.0004699725,0.002160069,0.0002314214],"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":[0.0002381937,0.0003959217,0.006615364,0.0009828821,0.0003161504,0.001310898,0.002329516,0.0762049,0.002971471,0.3433275,0.02454814,0.540759],"study_design_scores_gemma":[0.0001308075,0.0003162599,0.003498001,0.0004273835,0.00009737375,0.0007113972,0.001924995,0.5851256,0.003077905,0.3483565,0.05619032,0.000143527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01659257,0.0006672281,0.9487545,0.003515957,0.0002606887,0.00073907,0.0007647139,0.0009913816,0.02771377],"genre_scores_gemma":[0.1405908,0.0007006968,0.8539053,0.0001303021,0.0000604833,0.0004406651,0.0003333327,0.00005827104,0.003780136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01047904,"threshold_uncertainty_score":0.03685099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05886790145175001,"score_gpt":0.316906420037691,"score_spread":0.258038518585941,"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."}}