Diabetes
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Local explanation fidelity | Diabetes n = 9 | RMSE0.001 | 54 | |
| Classification | Diabetes (test) | Accuracy92.5 | 49 | |
| Classification | Diabetes | Mean Misclassification Rate22.05 | 48 | |
| Classification | Diabetes | Accuracy85.71 | 48 | |
| Conditional Shapley value estimation | Diabetes M=10 | MSEv0.125 | 43 | |
| Binary Classification | Diabetes | AUC0.84 | 34 | |
| Classification | Diabetes | F1 Score86.6 | 33 | |
| Contamination detection | diabetes | Acomp42 | 24 | |
| Counterfactual Explanation Generation | Diabetes | R0.996 | 23 | |
| State Reconstruction | diabetes Correlated Gaussian noise (test) | MSE0.963 | 20 | |
| Kernel State Reconstruction | diabetes Student-t noise (test) | Full Test MSE0.853 | 20 | |
| Faithful Narrative Generation | diabetes | RA0.975 | 16 | |
| Data Imputation | Diabetes (1/3 omitted) | Accuracy63.21 | 16 | |
| Classification | Diabetes130us | ROC-AUC0.6366 | 15 | |
| Tabular Data Synthesis | Diabetes | Shapes0.9966 | 15 | |
| Tabular Classification | diabetes 37 (test) | Test Error23.4 | 15 | |
| Tabular Classification with Feature Selection | Diabetes | Accuracy62.63 | 14 | |
| Tabular Classification | Diabetes (test) | Accuracy62.64 | 14 | |
| Data Imputation | Diabetes | Accuracy63.18 | 14 | |
| AUC maximization | diabetes (test) | AUC81.3 | 13 | |
| Classification | Diabetes 25% held-out (test) | Accuracy76 | 12 | |
| Counterfactual Explanation | diabetes | Validity100 | 12 | |
| Classification | diabetes (val) | AUROC (%)85.2 | 12 | |
| Explanation Regularity | Diabetes | Regularity97.8 | 11 | |
| Explanation Fidelity Estimation | Diabetes | Fidelity (R2 Score)0.92 | 11 |
Showing 25 of 97 rows