Binary Classification on Wisconsin Breast Cancer
99.9AUROCIS-ANN-L1
Evaluation results
| Method | Links | |
|---|---|---|
| IS-ANN-L1Model Sparsity=Full2025.03 | 99.9 | |
| IS-ANN-L1Model Sparsity=Sparse2025.03 | 99.9 | |
| ISLaB-LRTModel Sparsity=Full2025.03 | 99.8 | |
| ISLaB-LRTModel Sparsity=Sparse2025.03 | 99.8 | |
| ISLaB-FLOWModel Sparsity=Full2025.03 | 99.7 | |
| BLR-LRTModel Sparsity=Full2025.03 | 99.7 | |
| BLR-LRTModel Sparsity=Sparse2025.03 | 99.7 | |
| BLR-FLOWModel Sparsity=Sparse2025.03 | 99.6 | |
| ISLaB-FLOWModel Sparsity=Sparse2025.03 | 99.5 | |
| BLR-FLOWModel Sparsity=Full2025.03 | 99.5 | |
| FlagGAM + RF HeadGroup=Ours2026.05 | 99.3 | |
| XGBoostGroup=Tree2026.05 | 99.2 | |
| EBMGroup=Additive2026.05 | 99.1 | |
| BNN-HORSEModel Sparsity=Full2025.03 | 99.1 | |
| BNN-HORSEModel Sparsity=Sparse2025.03 | 99.1 | |
| Laplace-SpaMModel Sparsity=Sparse2025.03 | 99.1 | |
| BNN-CONCRETEModel Sparsity=Full2025.03 | 98.9 | |
| Laplace-SpaMModel Sparsity=Full2025.03 | 98.9 | |
| FlagGAMGroup=Ours2026.05 | 98.8 | |
| RFGroup=Tree2026.05 | 98.6 | |
| TabNetGroup=Deep2026.05 | 98.4 |