Diabetes
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Classification | Diabetes | Accuracy85.71 | 80 | |
| Local explanation fidelity | Diabetes n = 9 | RMSE0.001 | 54 | |
| Shapley interaction estimation | Diabetes | Cosine Similarity99.37 | 50 | |
| Classification | Diabetes (test) | Accuracy92.5 | 49 | |
| Classification | Diabetes | Mean Misclassification Rate22.05 | 48 | |
| Conditional Shapley value estimation | Diabetes M=10 | MSEv0.125 | 43 | |
| Binary Classification | Diabetes | AUC0.84 | 38 | |
| Class Prior Estimation | Diabetes | Estimation Error0.043 | 36 | |
| Interaction value estimation | Diabetes (test) | Time (s)0.0028 | 34 | |
| Classification | Diabetes | F1 Score86.6 | 33 | |
| Tabular Classification | Diabetes (test) | Accuracy82.94 | 32 | |
| Counterfactual Explanation Generation | Diabetes | L2 Error1.8 | 29 | |
| Counterfactual Explanation | diabetes | Validity100 | 28 | |
| Model Compression | diabetes | Accuracy / R2 Score80 | 26 | |
| Contamination detection | diabetes | Acomp42 | 24 | |
| Hyperparameter Optimization | Diabetes RF (test) | Final Simple Regret0.8926 | 22 | |
| State Reconstruction | diabetes Correlated Gaussian noise (test) | MSE0.963 | 20 | |
| Kernel State Reconstruction | diabetes Student-t noise (test) | Full Test MSE0.853 | 20 | |
| Regression | Diabetes dataset | R20.8 | 17 | |
| Faithful Narrative Generation | diabetes | RA0.975 | 16 | |
| Data Imputation | Diabetes (1/3 omitted) | Accuracy63.21 | 16 | |
| Counterfactual Explanations | diabetes | Validity49.8 | 15 | |
| Classification | Diabetes130us | ROC-AUC0.6366 | 15 | |
| Tabular Data Synthesis | Diabetes | Shapes0.9966 | 15 | |
| Tabular Classification | diabetes 37 (test) | Test Error23.4 | 15 |
Showing 25 of 150 rows