Binary Classification on Bank Marketing
0.932AUCXGBoost
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| XGBoost2025.07 | 0.932 | — | 0.002 | 0.002 | |
| SBN2025.07 | 0.914 | — | 0.005 | 0.002 | |
| Capmode=oracle-style upper bound2026.01 | 0.89 | — | — | — | |
| DP-FinDiffε-DP=102025.11 | 0.804 | — | — | — | |
| DP-FinDiffε-DP=12025.11 | 0.797 | — | — | — | |
| DP-TVAEε-DP=102025.11 | 0.773 | — | — | — | |
| DP-FinDiffε-DP=0.22025.11 | 0.757 | — | — | — | |
| LoIDmode=our method, backbone=Gemma-2-27B, alpha=0.2, gamma=2, N_sent=102026.01 | 0.72 | 56 | — | — | |
| DP-TVAEε-DP=12025.11 | 0.594 | — | — | — | |
| DP-TabDDPMε-DP=102025.11 | 0.579 | — | — | — | |
| DP-TVAEε-DP=0.22025.11 | 0.556 | — | — | — | |
| DP-TabDDPMε-DP=12025.11 | 0.537 | — | — | — | |
| DP-TabDDPMε-DP=0.22025.11 | 0.519 | — | — | — | |
| DP-CTGANε-DP=0.22025.11 | 0.517 | — | — | — | |
| DP-CTGANε-DP=102025.11 | 0.513 | — | — | — | |
| OOD-LRdescription=logistic regression trained on an OOD training set2026.01 | 0.51 | — | — | — | |
| AutoElicitmode=baseline2026.01 | 0.51 | — | — | — | |
| LLMProcmode=baseline2026.01 | 0.51 | — | — | — | |
| DP-CTGANε-DP=12025.11 | 0.458 | — | — | — |