Classification on German Credit (test)
77.66AccuracyXGBoost
Evaluation results
| Method | Links | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| XGBoost2021.06 | 77.66 | — | — | — | — | — | — | — | — | — | |
| RFBase Model=Random Forest, Fairness Mitigation Method=None2026.04 | 75.47 | — | — | — | — | — | — | — | 74.95 | 0.0265 | |
| RF + CAFPBase Model=Random Forest, Fairness Mitigation Method=Counterfactual Averaging for Fair Predictions2026.04 | 75.41 | — | — | — | — | — | — | — | 74.89 | 0.0263 | |
| XGB + CAFPBase Model=XGBoost, Fairness Mitigation Method=Counterfactual Averaging for Fair Predictions2026.04 | 74.91 | — | — | — | — | — | — | — | 74.39 | 0.026 | |
| XGBBase Model=XGBoost, Fairness Mitigation Method=None2026.04 | 74.82 | — | — | — | — | — | — | — | 74.28 | 0.0274 | |
| LRBase Model=Logistic Regression, Fairness Mitigation Method=None2026.04 | 74.15 | — | — | — | — | — | — | — | 73.59 | 0.0284 | |
| GDRODemographic Information Usage=Sensitive information in train & val2026.02 | 74.1 | 54.5 | 27 | 22.3 | 17.4 | 63.3 | 12.8 | — | — | — | |
| ARLDemographic Information Usage=Without demographics2026.02 | 74 | 60.9 | 19.5 | 19.8 | 21.4 | 64.2 | 11.5 | — | — | — | |
| RF + Eq.OddsBase Model=Random Forest, Fairness Mitigation Method=Equalized Odds2026.04 | 73.9 | — | — | — | — | — | — | — | 73.31 | 0.0298 | |
| LR + CAFPBase Model=Logistic Regression, Fairness Mitigation Method=Counterfactual Averaging for Fair Predictions2026.04 | 73.79 | — | — | — | — | — | — | — | 73.21 | 0.0293 | |
| XGBDemographic Information Usage=Baseline2026.02 | 73.5 | 55.1 | 23.3 | 20.7 | 13 | 65 | 10 | — | — | — | |
| XGB + Eq.OddsBase Model=XGBoost, Fairness Mitigation Method=Equalized Odds2026.04 | 72.92 | — | — | — | — | — | — | — | 72.17 | 0.0377 | |
| LRDemographic Information Usage=Baseline2026.02 | 72.7 | 54.7 | 25.8 | 27.4 | 21.4 | 58.4 | 16.8 | — | — | — | |
| LR + Eq.OddsBase Model=Logistic Regression, Fairness Mitigation Method=Equalized Odds2026.04 | 71.89 | — | — | — | — | — | — | — | 71.11 | 0.039 | |
| MMPFrelDemographic Information Usage=Sensitive information in train & val2026.02 | 71.8 | 56.7 | 25.1 | 25.3 | 17.3 | 63.1 | 12.4 | — | — | — | |
| XBNet2021.06 | 71.33 | — | — | — | — | — | — | — | — | — | |
| MMPFDemographic Information Usage=Sensitive information in train & val2026.02 | 71.3 | 49.8 | 30.1 | 24.5 | 18.9 | 62.9 | 13.2 | — | — | — | |
| SPECTRE+ACCDemographic Information Usage=Without demographics2026.02 | 71.1 | 62.9 | 17 | 20.9 | 22.6 | 64.3 | 8 | — | — | — | |
| SPECTRE+TOPN+WCEDemographic Information Usage=Without demographics2026.02 | 70.6 | 62 | 13 | 16.5 | 18.4 | 68.4 | 3.6 | — | — | — | |
| SPECTRE+WCEDemographic Information Usage=Without demographics2026.02 | 70.5 | 61.4 | 16.2 | 22.1 | 22.4 | 63 | 9.8 | — | — | — | |
| RF + R. O.Base Model=Random Forest, Fairness Mitigation Method=Reject Option2026.04 | 70.46 | — | — | — | — | — | — | — | 69.57 | 0.0453 | |
| SPECTRE+WCE+T+ADemographic Information Usage=Without demographics2026.02 | 70.4 | 61.6 | 19.6 | 26.4 | 18.9 | 61.1 | 9.6 | — | — | — | |
| XGB + R. O.Base Model=XGBoost, Fairness Mitigation Method=Reject Option2026.04 | 69.31 | — | — | — | — | — | — | — | 68.39 | 0.0464 | |
| LR + R. O.Base Model=Logistic Regression, Fairness Mitigation Method=Reject Option2026.04 | 68.42 | — | — | — | — | — | — | — | 67.54 | 0.044 | |
| SUREDemographic Information Usage=Without demographics2026.02 | 65.9 | 54.5 | 15.2 | 6.2 | 4.6 | 58.4 | 9.8 | — | — | — | |
| RLMDemographic Information Usage=Without demographics2026.02 | 54.9 | 46.5 | 21.4 | 25.3 | 26.3 | 48.4 | 11.1 | — | — | — | |
| FairEnsDemographic Information Usage=Without demographics2026.02 | 52.7 | 44 | 13.5 | 8.2 | 9.6 | 49.2 | 9 | — | — | — | |
| BPFDemographic Information Usage=Without demographics2026.02 | 47.1 | 41.4 | 16.8 | 35.7 | 38 | 43.8 | 10 | — | — | — | |
| DTE-1variant=DTE-12025.12 | — | — | — | — | — | — | — | 23.6 | — | — | |
| DTE-3variant=DTE-32025.12 | — | — | — | — | — | — | — | 23.4 | — | — | |
| Forest2025.12 | — | — | — | — | — | — | — | 23.5 | — | — | |
| S-NN2025.12 | — | — | — | — | — | — | — | 29.6 | — | — | |
| Tree2025.12 | — | — | — | — | — | — | — | 30.4 | — | — |