pima
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Tabular Anomaly Detection | Pima | AUC ROC0.7818 | 70 | |
| Classification | pima | Accuracy78.6 | 52 | |
| Binary Classification | pima | F1-score96.15 | 27 | |
| Classification | Pima | AUC0.787 | 18 | |
| Outlier Detection | Pima ADBench | AUROC72.53 | 17 | |
| Execution time measurement | Pima 50% MNAR | Training Time (s)0.147 | 15 | |
| Classification | pima 25% feature noise | Accuracy77.5 | 14 | |
| Classification | pima | F1-score84.3 | 14 | |
| Outlier Detection | Pima (Group I) | AUROC72.53 | 14 | |
| Binary Classification | pima 25% label noise | Mean F1-score0.838 | 14 | |
| Binary Classification | pima 25% feature noise | F1 Score83.9 | 14 | |
| Classification | Pima 20% | PR AUC0.527 | 12 | |
| Classification | Pima | PR AUC71.3 | 12 | |
| Imbalanced Classification | Pima (test) | Macro F176.31 | 12 | |
| Classification | Pima | Recall77.03 | 12 | |
| Anomaly Detection | PIMA ODDS | AUC72.2 | 12 | |
| Classification | Pima | Precision76.73 | 11 | |
| Outlier Detection | Pima | AP53.57 | 11 | |
| Anomaly Detection | pima In-Domain | F1 Score69.1 | 10 | |
| Outlier Detection | Pima | Precision-s54.85 | 9 | |
| Continual Clustering | Pima | AI NMI0.572 | 9 | |
| Classification | pima 0% noise (test) | Accuracy77.3 | 7 | |
| Classification | pima 0% noise | F1-score84.7 | 7 | |
| Binary Classification | pima 25% label noise (test) | Accuracy77.9 | 7 | |
| Binary classification | pima UCI (test) | Accuracy77.1 | 7 |
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