Binary Classification on Diabetes (test)
0.4831LossOEHG
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| OEHGModel Type=Logistic Regression2026.02 | 0.4831 | 77.28 | — | |
| OEHGModel Type=Support Vector Machine2026.02 | 0.5244 | 78.13 | — | |
| AID-CGModel Type=Logistic Regression2026.02 | 0.6054 | 70.94 | — | |
| RHGModel Type=Logistic Regression2026.02 | 0.6409 | 68.38 | — | |
| RHGModel Type=Support Vector Machine2026.02 | 0.6434 | 69.87 | — | |
| T-RHGModel Type=Logistic Regression2026.02 | 0.6458 | 68.38 | — | |
| T-RHGModel Type=Support Vector Machine2026.02 | 0.7472 | 68.38 | — | |
| APLRType=Piecewise-linear GAM2026.04 | — | — | 0.387 | |
| EBMType=Tree-based GAM2026.04 | — | — | 0.379 | |
| Linear/Logistic regressionImplementation=scikit-learn2026.04 | — | — | 0.416 | |
| MGCVImplementation=PyMGCV, Bases=CubicSpline2026.04 | — | — | 0.416 | |
| NAMArchitecture=MLP (64, 64, 32), Optimizer=AdamW2026.04 | — | — | 0.387 | |
| NBMArchitecture=100 shared basis functions, Optimizer=AdamW2026.04 | — | — | 0.385 | |
| ParamBoostImplementation=JAX2026.04 | — | — | 0.38 |