Anomaly Detection on Vehicle Claims
0Training TimeNon-parametric MaskDiff-AD
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Non-parametric MaskDiff-ADModel Type=Non-parametric2026.05 | 0 | 3,005.69 | 3,005.69 | |
| Hamming-kNN2026.05 | 0 | 65.66 | 65.66 | |
| COPOD2026.05 | 0.13 | 0.22 | 0.35 | |
| ECOD2026.05 | 0.24 | 0.25 | 0.49 | |
| IForest2026.05 | 0.35 | 1.35 | 1.7 | |
| Parametric MaskDiff-ADModel Type=Parametric2026.05 | 31.64 | 16.28 | 47.92 | |
| DTE-Gaussian2026.05 | 130.23 | 0.24 | 130.47 | |
| DeepSVDD2026.05 | 130.88 | 0.2 | 131.09 | |
| DRL2026.05 | 132.68 | 0.12 | 132.8 | |
| DTE-Categorical2026.05 | 138.35 | 0.25 | 138.59 | |
| DTE-InvGamma2026.05 | 144.01 | 0.25 | 144.27 | |
| MCM2026.05 | 678.01 | 0.63 | 678.64 | |
| GOAD2026.05 | 768.66 | 22.35 | 791.02 | |
| ICL2026.05 | 817.37 | 2.02 | 819.39 |