bank-marketing
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Classification | Bank Marketing (BM) (test) | Macro F1 Score91.2 | 36 | |
| Binary Classification | Bank Marketing public (CV) | F1 Score66.6 | 33 | |
| Classification | Bank Marketing | ROC AUC0.934 | 19 | |
| Binary Classification | Bank Marketing | AUC0.932 | 19 | |
| Backdoor Defense | Bank marketing (test) | Misclassification Accuracy86 | 18 | |
| Classification | bank-marketing | Accuracy90.91 | 18 | |
| Counterfactual Recourse | Bank Marketing | Recourse Cost0.17 | 16 | |
| Classification | bank-marketing | Cohen's Kappa0.7 | 16 | |
| Machine Learning | Bank Marketing | F1 Score88.5 | 15 | |
| Classification | bank-marketing (5-fold cross-validation) | Macro F1 Score76.32 | 12 | |
| Selective Classification | Bank Marketing | AU-ARC94.87 | 10 | |
| Tabular Classification | Bank Marketing (test) | Accuracy0.9198 | 10 | |
| Unfairness Witness Finding | Bank Marketing Age | Bias (%)0 | 8 | |
| Tabular Synthetic Data Generation | Bank Marketing | KS Statistic0.013 | 8 | |
| Active Learning | Bank-Marketing | AULC25.8 | 8 | |
| Classification | bank-marketing 1461 | AUROC93.7 | 8 | |
| Tabular Data Generation | Bank Marketing | Peak GPU Memory Usage (GB)2.4 | 7 | |
| Classification | Bank Marketing | EO Gap0.05 | 7 | |
| Distribution Alignment | Bank Marketing | MMD0.0226 | 7 | |
| Classification | Bank Marketing (holdout) | Mean Brier Score0.0881 | 5 | |
| Classification | Bank Marketing mean across 26 outer seeds (holdout) | Brier Score0.0881 | 5 | |
| Classification | bank-marketing | Accuracy89.6 | 5 | |
| Federated U-statistics computation | Synthetic and Bank Marketing | MSE1 | 5 | |
| Classification | Bank Marketing (test) | Classification Error Rate9.5 | 5 | |
| Binary Classification | Bank Marketing (test) | Macro F1 Score64 | 4 |
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