Outlier Detection on IoT (test)
97.28AUCmeta-learning for relative DRE
Evaluation results
| Method | Links | |
|---|---|---|
| meta-learning for relative DRENumber of target normal support instances=12021.07 | 97.28 | |
| meta-learning for relative DREarchitecture=three-layered feed-forward neural network2021.07 | 96.94 | |
| uLSIFNumber of target normal support instances=12021.07 | 95.87 | |
| RuLSIFNumber of target normal support instances=12021.07 | 95.75 | |
| KL2021.07 | 94.79 | |
| LOFNumber of target normal support instances=12021.07 | 93.3 | |
| RuLSIF-FTNumber of target normal support instances=12021.07 | 93.15 | |
| AENumber of target normal support instances=12021.07 | 93.09 | |
| SDNumber of target normal support instances=12021.07 | 91.9 | |
| nnPU2021.07 | 91.18 | |
| D3RENumber of target normal support instances=12021.07 | 85.2 | |
| D3RE-FTNumber of target normal support instances=12021.07 | 84.51 | |
| AE-FTNumber of target normal support instances=12021.07 | 66.05 | |
| SD-FTNumber of target normal support instances=12021.07 | 55.5 | |
| AE-SNumber of target normal support instances=12021.07 | 43.59 | |
| IFNumber of target normal support instances=12021.07 | 41.32 | |
| SD-SNumber of target normal support instances=12021.07 | 40.12 |