{"id":"W2426566611","doi":"10.5539/ibr.v9n7p164","title":"Comparing the Performance of Different Data Mining Techniques in Evaluating Loan Applications","year":2016,"lang":"en","type":"article","venue":"International Business Research","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Loan; Computer science; Decision tree; Random forest; Classifier (UML); Cart; Artificial intelligence; Machine learning; Statistics; Data mining; Actuarial science; Econometrics; Business; Mathematics; Finance; Engineering","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":[0.007545848,0.0006664473,0.0007543791,0.006688389,0.0003983498,0.001475195,0.0004882056,0.0008558962,0.000631192],"category_scores_gemma":[0.02558678,0.000149532,0.0008439115,0.003444054,0.0002374466,0.001578467,0.0003932658,0.000611669,0.0005100819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005957028,"about_ca_system_score_gemma":0.000526907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004454855,"about_ca_topic_score_gemma":0.004103353,"domain_scores_codex":[0.9961093,0.001684654,0.0005309955,0.0003663684,0.001121337,0.000187336],"domain_scores_gemma":[0.9656618,0.02792511,0.001345113,0.0008784328,0.003822019,0.0003676437],"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":[0.002126193,0.001039649,0.2243266,0.0005053156,0.0005870163,0.0001457393,0.0004489634,0.03541561,0.006076848,0.0006420208,0.003241863,0.7254443],"study_design_scores_gemma":[0.0001372931,0.004413277,0.2785482,0.0002407274,0.000510157,0.0005616473,0.001550711,0.6859986,0.02039357,0.002408063,0.005089315,0.0001483722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9374822,0.002779468,0.04959987,0.0006813628,0.0001611828,0.0002522002,0.001197003,0.0009284677,0.006918324],"genre_scores_gemma":[0.9539102,0.0006219026,0.04349172,0.00006859077,0.0000553878,0.00007354098,0.0008755198,0.00002523486,0.0008778638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007545848,"threshold_uncertainty_score":0.03990674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1694375608733418,"score_gpt":0.3956436650767899,"score_spread":0.2262061042034481,"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."}}