Table 4.
Saturated performances of stochastic channel-based federated learning with pruning when the total pruned proportion was fixed and the pruning rate for each training loop changed.
| Pruning rate/loop | AUC-ROCa | AUC-PRb |
| 10% | 0.9765 | 0.9661 |
| 20% | 0.9730 | 0.9568 |
| 30% | 0.9763 | 0.9662 |
| 40% | 0.9693 | 0.9465 |
| 50% | 0.9769 | 0.9663 |
aAUC-ROC: area under the receiver operating characteristic curve.
bAUC-PR: area under the precision-recall curve.