Trajectory Classification on Car Traffic Dataset
87.01Weighted F1-scoreOutlierness-Based Selection
Evaluation results
| Method | Links | |
|---|---|---|
| Outlierness-Based SelectionML Model=XGBoost, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 87.01 | |
| Diversity Maximization SelectionML Model=XGBoost, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 86.55 | |
| Representativeness-Based SelectionML Model=MLP, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 86.05 | |
| BaselineML Model=XGBoost2026.06 | 85.89 | |
| Diversity Maximization SelectionML Model=MLP, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 85.64 | |
| Representativeness-Based SelectionML Model=LogisticReg, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 85.1 | |
| Diversity Maximization SelectionML Model=LogisticReg, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 85.08 | |
| Uncertainty-Based SelectionML Model=MLP, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 84.99 | |
| RandomML Model=XGBoost, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 84.95 | |
| Outlierness-Based SelectionML Model=LogisticReg, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 84.87 | |
| BaselineML Model=LogisticReg2026.06 | 84.69 | |
| Outlierness-Based SelectionML Model=MLP, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 84.53 | |
| RandomML Model=LogisticReg, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 84.44 | |
| BaselineML Model=MLP2026.06 | 84.39 | |
| Representativeness-Based SelectionML Model=XGBoost, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 84.35 | |
| Uncertainty-Based SelectionML Model=XGBoost, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 83.92 | |
| RandomML Model=MLP, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 83.87 | |
| Uncertainty-Based SelectionML Model=LogisticReg, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 83.41 | |
| Diversity Maximization SelectionML Model=RandomForest, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 82.96 | |
| RandomML Model=RandomForest, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 82.57 | |
| Uncertainty-Based SelectionML Model=RandomForest, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 82.38 | |
| BaselineML Model=RandomForest2026.06 | 82.28 | |
| Outlierness-Based SelectionML Model=RandomForest, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 82.18 | |
| Representativeness-Based SelectionML Model=RandomForest, Selection Proportion (Sel)=20%, Number of Augmentations (Augs)=3, Point modification proportion (Pts)=10%2026.06 | 82.18 |