Outlier Detection on Mushroom 2
96.23APDevNet
Evaluation results
| Method | Links | |
|---|---|---|
| DevNetlabeled data ratio=1%2025.12 | 96.23 | |
| PReNetlabeled data ratio=1%2025.12 | 95.11 | |
| FRODlabeled data ratio=1%2025.12 | 94.69 | |
| GDOFlabeled outliers=52025.12 | 91.5 | |
| FEAWADlabeled data ratio=1%2025.12 | 86.72 | |
| DevNetlabeled outliers=52025.12 | 83.5 | |
| PReNetlabeled outliers=52025.12 | 82.8 | |
| FEAWADlabeled outliers=52025.12 | 77.8 | |
| WFRDAlabeled data ratio=1%2025.12 | 67.43 | |
| WFRDAlabeled outliers=52025.12 | 67.3 | |
| DeepSADlabeled outliers=52025.12 | 61 | |
| LUNARlabeled outliers=52025.12 | 58.3 | |
| IForestlabeled data ratio=1%2025.12 | 50.9 | |
| MFGADlabeled data ratio=1%2025.12 | 44.84 | |
| REPENlabeled outliers=52025.12 | 40.1 | |
| DeepSVDDlabeled outliers=52025.12 | 39.8 | |
| DeepSADlabeled data ratio=1%2025.12 | 38.55 | |
| REPENlabeled data ratio=1%2025.12 | 38.42 | |
| ECODlabeled outliers=52025.12 | 36.5 | |
| DeepSVDDlabeled data ratio=1%2025.12 | 30.77 | |
| DIFlabeled outliers=52025.12 | 18.9 | |
| ECODlabeled data ratio=1%2025.12 | 11.98 |