Anomaly Detection on SMAP (P, R, F1, Avg F1)
94.75PrecisionMAAT
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| MAAT2025.02 | 94.75 | 99.33 | 96.99 | — | |
| DCdetector2025.02 | 94.29 | 97.97 | 96.1 | — | |
| Anomaly Trans2025.02 | 93.59 | 99.41 | 96.41 | — | |
| BeatGAN2025.02 | 92.38 | 55.85 | 69.61 | — | |
| LSTM-VAE2025.02 | 92.2 | 67.75 | 78.1 | — | |
| THOC2025.02 | 92.06 | 89.34 | 90.68 | — | |
| LSTM2025.02 | 91 | 81.89 | 86.21 | — | |
| TS-CP22025.02 | 86.75 | 83.18 | 84.95 | — | |
| DAGMM2025.02 | 86.45 | 56.73 | 68.51 | — | |
| BOCPD2025.02 | 86.45 | 85.85 | 86.14 | — | |
| MMPCACD2025.02 | 83.22 | 68.23 | 74.73 | — | |
| ITAD2025.02 | 82.42 | 66.89 | 73.85 | — | |
| OmniAnomaly2025.02 | 81.42 | 84.3 | 82.83 | — | |
| VAR2025.02 | 81.38 | 53.88 | 64.83 | — | |
| CL-MPPCA2025.02 | 63.16 | 72.88 | 67.72 | — | |
| LOF2025.02 | 58.93 | 56.33 | 57.6 | — | |
| Deep-SVDD2025.02 | 56.02 | 69.04 | 62.4 | — | |
| OCSVM2025.02 | 53.85 | 59.07 | 56.34 | — | |
| Forrest2025.02 | 52.39 | 55.53 | 53.89 | — | |
| U-Time2025.02 | 49.71 | 56.18 | 52.75 | — |