Multi-view Anomaly Detection on Synthetic Dataset Uniform density
1AUCSCoNE
Evaluation results
| Method | Links | ||
|---|---|---|---|
| SCoNEensemble size t=2002025.12 | 1 | 87.6 | |
| MODDISArchitecture=Deep learning-based2025.12 | 0.997 | 85.5 | |
| IAMOD2025.12 | 0.995 | 82.3 | |
| MODGF2025.12 | 0.994 | 83.5 | |
| NCMODArchitecture=Deep learning-based2025.12 | 0.986 | 81.7 | |
| HBMLearning Paradigm=Semi-supervised2025.12 | 0.981 | — | |
| ECMOD2025.12 | 0.977 | 79.1 | |
| MODGD2025.12 | 0.954 | 76.8 | |
| iForestInput View=Single-view (Concatenated)2025.12 | 0.896 | — |