Node Regression on Chameleon
0.484Normalized MAE LossFIT-GNN
Evaluation Results
| Method | Links | |
|---|---|---|
| FIT-GNNBackbone=SAGE, Reduction Ratio (r)=0.5, Method Appending Nodes=Cluster Nodes2024.10 | 0.484 | |
| FIT-GNNBackbone=SAGE, Reduction Ratio (r)=0.3, Method Appending Nodes=Cluster Nodes2024.10 | 0.489 | |
| FIT-GNNBackbone=GCN, Reduction Ratio (r)=0.1, Method Appending Nodes=Cluster Nodes2024.10 | 0.496 | |
| FIT-GNNBackbone=SAGE, Reduction Ratio (r)=0.1, Method Appending Nodes=Cluster Nodes2024.10 | 0.506 | |
| FIT-GNNBackbone=GCN, Reduction Ratio (r)=0.3, Method Appending Nodes=Cluster Nodes2024.10 | 0.531 | |
| FIT-GNNBackbone=GCN, Reduction Ratio (r)=0.5, Method Appending Nodes=Cluster Nodes2024.10 | 0.531 | |
| FIT-GNNBackbone=GCN, Reduction Ratio (r)=0.7, Method Appending Nodes=Cluster Nodes2024.10 | 0.536 | |
| FIT-GNNBackbone=GAT, Reduction Ratio (r)=0.3, Method Appending Nodes=Cluster Nodes2024.10 | 0.537 | |
| FIT-GNNBackbone=SAGE, Reduction Ratio (r)=0.7, Method Appending Nodes=Cluster Nodes2024.10 | 0.539 | |
| FIT-GNNBackbone=GAT, Reduction Ratio (r)=0.5, Method Appending Nodes=Cluster Nodes2024.10 | 0.556 | |
| FIT-GNNBackbone=GAT, Reduction Ratio (r)=0.7, Method Appending Nodes=Cluster Nodes2024.10 | 0.576 | |
| FIT-GNNBackbone=GAT, Reduction Ratio (r)=0.1, Method Appending Nodes=Cluster Nodes2024.10 | 0.582 | |
| FIT-GNNBackbone=GIN, Reduction Ratio (r)=0.1, Method Appending Nodes=Cluster Nodes2024.10 | 0.769 | |
| FIT-GNNBackbone=GIN, Reduction Ratio (r)=0.7, Method Appending Nodes=Cluster Nodes2024.10 | 0.792 | |
| FIT-GNNBackbone=GIN, Reduction Ratio (r)=0.3, Method Appending Nodes=Cluster Nodes2024.10 | 0.808 | |
| FIT-GNNBackbone=GIN, Reduction Ratio (r)=0.5, Method Appending Nodes=Cluster Nodes2024.10 | 0.81 | |
| GINSetup=Full, Reduction Ratio (r)=1.02024.10 | 0.843 | |
| GATSetup=Full, Reduction Ratio (r)=1.02024.10 | 0.846 | |
| SAGESetup=Full, Reduction Ratio (r)=1.02024.10 | 0.848 | |
| GCNSetup=Full, Reduction Ratio (r)=1.02024.10 | 0.852 |