Classification on Steel-Plates
90.6ROC AUCTabPFN-Hybrid
Evaluation Results
| Method | Links | |
|---|---|---|
| TabPFN-HybridActive Learning Strategy=Hybrid, Backbone=TabPFN, Label Budget=100, Batch Size=102026.03 | 90.6 | |
| TabPFN-MarginActive Learning Strategy=Margin, Backbone=TabPFN, Label Budget=100, Batch Size=102026.03 | 90.6 | |
| TabPFN-RandomActive Learning Strategy=Random, Backbone=TabPFN, Label Budget=100, Batch Size=102026.03 | 90 | |
| TabPFN-Proxy-HybridActive Learning Strategy=Proxy-Hybrid, Backbone=TabPFN, Label Budget=100, Batch Size=102026.03 | 89.1 | |
| TabPFN-CoresetActive Learning Strategy=Coreset, Backbone=TabPFN, Label Budget=100, Batch Size=102026.03 | 88.9 | |
| CatBoost-MarginActive Learning Strategy=Margin, Backbone=CatBoost, Label Budget=100, Batch Size=102026.03 | 88.4 | |
| LabelSpreading-RandomActive Learning Strategy=Random, Backbone=LabelSpreading, Label Budget=100, Batch Size=102026.03 | 85.5 | |
| XGBoost-MarginActive Learning Strategy=Margin, Backbone=XGBoost, Label Budget=100, Batch Size=102026.03 | 84.6 |