Multiple Instance Learning Classification on FOX
96.1AccuracyASMIL
Evaluation Results
| Method | Links | |
|---|---|---|
| ASMIL2026.03 | 96.1 | |
| RGMIL2026.03 | 95.4 | |
| ABMIL2026.03 | 95.2 | |
| TransMIL2026.03 | 94.4 | |
| PSMIL2026.03 | 94.2 | |
| DEMIL2026.03 | 94.1 | |
| DSMIL2026.03 | 93.9 | |
| TG-RGMIL [0,1,2]DTopological features=0D, 1D, 2D2023.07 | 79.2 | |
| APMILwD (2025)Reference Year=20252023.07 | 78.9 | |
| GAPMILwD (2025)Reference Year=20252023.07 | 78.8 | |
| TG-RGMIL [0,1]DTopological features=0D, 1D2023.07 | 78.5 | |
| TG-RGMIL [0]DTopological features=0D2023.07 | 74.7 | |
| DSMIL (2021)Reference Year=20212023.07 | 72.9 | |
| RGMIL (2023)Reference Year=20232023.07 | 71.4 | |
| DistNet (2023)Reference Year=20232023.07 | 68 | |
| GNNMIL (2019)Reference Year=20192023.07 | 67.9 | |
| MI-ANFIS2016.10 | 66.4 | |
| ALP-SVM2016.10 | 66 | |
| DPMIL (2018)Reference Year=20182023.07 | 65.5 | |
| MIForest2016.10 | 64 | |
| BDRMIL (2022)Reference Year=20222023.07 | 62.9 | |
| miGraph2016.10 | 61.6 | |
| APMIL (2018)Reference Year=20182023.07 | 61.5 | |
| MIGraph2016.10 | 61.2 | |
| GAPMIL (2018)Reference Year=20182023.07 | 60.3 | |
| MI-kernel2016.10 | 60.3 | |
| PPPM-kernel2016.10 | 60.3 | |
| mi-SVM2016.10 | 58.2 | |
| MI-SVM2016.10 | 57.8 | |
| EM-DD2016.10 | 56.1 |