Multiple Instance Learning Classification on MUSK1
98.2Accuracy
TG-RGMIL [0,1,2]D
Updated 1mo ago
Evaluation Results
| Method | Links | ||
|---|---|---|---|
2023.07 | 98.2 | - | |
2026.03 | 97.1 | - | |
2026.03 | 96.8 | - | |
2026.03 | 96.8 | - | |
2023.07 | 96.7 | - | |
2023.07 | 96.6 | - | |
2023.07 | 96.4 | - | |
2026.03 | 96.3 | - | |
2024.08 | 96.1 | 98.9 | |
2026.03 | 95.9 | - | |
2016.10 | 95.6 | - | |
2023.07 | 94.6 | - | |
2023.07 | 94 | - | |
2016.10 | 93.49 | - | |
2023.07 | 93.2 | - | |
2016.10 | 92.8 | - | |
2026.03 | 92.7 | - | |
2023.07 | 92.6 | - | |
2016.10 | 92.4 | - | |
2016.10 | 92.4 | - | |
2023.07 | 92.3 | - | |
2023.07 | 91.7 | - | |
2026.03 | 91.6 | - | |
2016.10 | 91.3 | - | |
2023.07 | 90.7 | - | |
2016.10 | 90.3 | - | |
2023.07 | 90 | - | |
2016.10 | 90 | - | |
2023.07 | 89.2 | - | |
2016.10 | 88.9 | - | |
2016.10 | 88.9 | - | |
2016.10 | 88 | - | |
2016.10 | 88 | - | |
2016.10 | 87.4 | - | |
2016.10 | 86.3 | - | |
2016.10 | 86.3 | - | |
2016.10 | 85.8 | - | |
2016.10 | 85 | - | |
2016.10 | 84.8 | - | |
2016.10 | 83.7 | - | |
2024.08 | 83.1 | 83.7 | |
2024.08 | 82.6 | 82.4 | |
2024.08 | 80 | 86.9 | |
2024.08 | 78.6 | 85.2 | |
2016.10 | 77.9 | - | |
2024.08 | 72.8 | 79.9 | |
2026.06 | - | 91.6 | |
2026.06 | - | 94.7 | |
2026.06 | - | 85.7 | |
2026.06 | - | 91.1 | |
2026.06 | - | 92.5 | |
2026.06 | - | 88 | |
2026.06 | - | 91 | |
2026.06 | - | 93.9 | |
2026.06 | - | 90.3 | |
2026.06 | - | 87 | |
2026.06 | - | 76.7 | |
2026.06 | - | 40.6 | |
2026.06 | - | 92.5 | |
2026.06 | - | 93.3 |