Image Classification on Emnist-Digits Non-IID D
99.1Convergence AccuracyFedACT
Evaluation results
| Method | Links | ||
|---|---|---|---|
| FedACTModel Architecture=LeNet-5, Local epochs=5, Mini-batch size=64, Target Accuracy=0.9842026.03 | 99.1 | 15.02 | |
| RandomModel Architecture=LeNet-5, Local epochs=5, Mini-batch size=64, Target Accuracy=0.9842026.03 | 99 | 42.56 | |
| MJ-FLModel Architecture=LeNet-5, Local epochs=5, Mini-batch size=64, Target Accuracy=0.9842026.03 | 99 | 21.87 | |
| GreedyModel Architecture=LeNet-5, Local epochs=5, Mini-batch size=64, Target Accuracy=0.9842026.03 | 98.7 | 42.73 | |
| GeneticModel Architecture=LeNet-5, Local epochs=5, Mini-batch size=64, Target Accuracy=0.9842026.03 | 98.6 | 31.28 |