Binary Classification on UNSW-NB15 (test)
96.89F1-scoreGTCN-G
Evaluation results
| Method | Links | |
|---|---|---|
| GTCN-GAttention mechanism=6-head, Dropout rate=0.52025.10 | 96.89 | |
| GATMode=Standard2025.10 | 94.56 | |
| E-GraphSAGE-MImplementation=mini-batching, Number of Layers=2, Aggregator=mean, Activation=ReLU, Sampling strategy=2-hop neighborhood, Sample size=8 per hop2025.10 | 92.34 | |
| E-GraphSAGE2025.10 | 90.23 |