Multi-view Anomaly Detection on Synthetic Dataset Varied densities
1AUCSCoNE
Evaluation results
| Method | Links | ||
|---|---|---|---|
| SCoNEensemble size t=2002025.12 | 1 | 86.9 | |
| MODDISArchitecture=Deep learning-based2025.12 | 0.952 | 78.6 | |
| MODGF2025.12 | 0.94 | 76.3 | |
| IAMOD2025.12 | 0.936 | 77.9 | |
| ECMOD2025.12 | 0.933 | 75.4 | |
| NCMODArchitecture=Deep learning-based2025.12 | 0.932 | 74.9 | |
| HBMLearning Paradigm=Semi-supervised2025.12 | 0.925 | — | |
| MODGD2025.12 | 0.907 | 69.1 | |
| iForestInput View=Single-view (Concatenated)2025.12 | 0.835 | — |