Anomaly Detection on FSB Sine
85AUCtcNF-base
Evaluation results
| Method | Links | |
|---|---|---|
| tcNF-baseCategory=Deep learning, Logic=Distribution2026.03 | 85 | |
| tcNF-mlpCategory=Deep learning, Logic=Distribution2026.03 | 83 | |
| tcNF-cnnCategory=Deep learning, Logic=Distribution2026.03 | 83 | |
| GDNCategory=Deep learning, Logic=Forecasting2026.03 | 82 | |
| PCACategory=Classic machine learning, Logic=Reconstruction2026.03 | 81 | |
| RealNVPCategory=Deep learning, Logic=Distribution2026.03 | 79 | |
| tcNF-statelessCategory=Deep learning, Logic=Distribution2026.03 | 78 | |
| KNNCategory=Classic machine learning, Logic=Distance2026.03 | 77 | |
| CBLOFCategory=Outlier detection, Logic=Distance2026.03 | 77 | |
| COFCategory=Outlier detection, Logic=Distance2026.03 | 73 | |
| TorskCategory=Deep learning, Logic=Forecasting2026.03 | 72 | |
| iForestCategory=Outlier detection, Logic=Trees2026.03 | 71 | |
| IF-LOFCategory=Outlier detection, Logic=Trees2026.03 | 71 | |
| DAMPCategory=Outlier detection, Logic=Distance2026.03 | 61 | |
| HBOSCategory=Outlier detection, Logic=Distance2026.03 | 55 | |
| PCCCategory=Classic machine learning, Logic=Reconstruction2026.03 | 37 |