Outlier Detection on Musk
100APFROD
Evaluation results
| Method | Links | |
|---|---|---|
| FRODlabeled data ratio=1%2025.12 | 100 | |
| GDOFlabeled outliers=52025.12 | 100 | |
| WFRDAlabeled data ratio=1%2025.12 | 99.52 | |
| WFRDAlabeled outliers=52025.12 | 98.1 | |
| REPENlabeled outliers=52025.12 | 97.2 | |
| PReNetlabeled outliers=52025.12 | 94.5 | |
| FEAWADlabeled outliers=52025.12 | 90.2 | |
| DIFlabeled outliers=52025.12 | 89.6 | |
| DeepSADlabeled outliers=52025.12 | 89.3 | |
| DeepSADlabeled data ratio=1%2025.12 | 83.25 | |
| PReNetlabeled data ratio=1%2025.12 | 81.58 | |
| DevNetlabeled outliers=52025.12 | 80.2 | |
| MFGADlabeled data ratio=1%2025.12 | 73.9 | |
| FEAWADlabeled data ratio=1%2025.12 | 70.42 | |
| LUNARlabeled outliers=52025.12 | 64.6 | |
| ECODlabeled outliers=52025.12 | 50.4 | |
| REPENlabeled data ratio=1%2025.12 | 49.93 | |
| ECODlabeled data ratio=1%2025.12 | 49.27 | |
| DeepSVDDlabeled data ratio=1%2025.12 | 38.39 | |
| DeepSVDDlabeled outliers=52025.12 | 30.7 | |
| IForestlabeled data ratio=1%2025.12 | 28.28 | |
| DevNetlabeled data ratio=1%2025.12 | 15.41 |