Node Classification on Citeseer semi-supervised (test)
68.59AccuracyAPPNP
Evaluation results
| Method | Links | ||
|---|---|---|---|
| APPNPLearning Setting=Semi-supervised2022.12 | 68.59 | — | |
| NFGNNLearning Setting=Semi-supervised2022.12 | 67.74 | — | |
| GPRGNNLearning Setting=Semi-supervised2022.12 | 67.63 | — | |
| GCNLearning Setting=Semi-supervised2022.12 | 67.3 | — | |
| GATLearning Setting=Semi-supervised2022.12 | 67.2 | — | |
| FAGCNLearning Setting=Semi-supervised2022.12 | 66.77 | — | |
| ReVarBackbone=GAT, Imbalance Ratio (p)=102023.10 | 66.04 | 65.7 | |
| BernNetLearning Setting=Semi-supervised2022.12 | 65.83 | — | |
| ChebNetLearning Setting=Semi-supervised2022.12 | 65.67 | — | |
| ReVarBackbone=GCN, Imbalance Ratio (p)=102023.10 | 65.28 | 64.91 | |
| BMGCNLearning Setting=Semi-supervised2022.12 | 64.34 | — | |
| ReVarBackbone=GraphSAGE, Imbalance Ratio (p)=102023.10 | 60.48 | 57.99 | |
| GraphENS + TAMBackbone=GCN, Imbalance Ratio (p)=102023.10 | 58.01 | 56.32 | |
| BalancedSoftmax + TAMBackbone=GCN, Imbalance Ratio (p)=102023.10 | 56.73 | 56.15 | |
| GraphENSBackbone=GCN, Imbalance Ratio (p)=102023.10 | 56.57 | 55.29 | |
| BalancedSoftmaxBackbone=GCN, Imbalance Ratio (p)=102023.10 | 55.52 | 53.74 | |
| MLPLearning Setting=Semi-supervised2022.12 | 52.88 | — | |
| PC SoftmaxBackbone=GCN, Imbalance Ratio (p)=102023.10 | 50.18 | 46.14 | |
| Renode + TAMBackbone=GCN, Imbalance Ratio (p)=102023.10 | 46.2 | 39.96 | |
| GraphSMOTEBackbone=GCN, Imbalance Ratio (p)=102023.10 | 44.87 | 39.2 | |
| Re-WeightBackbone=GCN, Imbalance Ratio (p)=102023.10 | 44.69 | 38.61 | |
| RenodeBackbone=GCN, Imbalance Ratio (p)=102023.10 | 43.47 | 37.52 | |
| VanillaBackbone=GraphSAGE, Imbalance Ratio (p)=102023.10 | 43.18 | 36.66 | |
| VanillaBackbone=GAT, Imbalance Ratio (p)=102023.10 | 38.84 | 31.25 | |
| VanillaBackbone=GCN, Imbalance Ratio (p)=102023.10 | 38.72 | 28.74 | |
| LINKLearning Setting=Semi-supervised2022.12 | 25.52 | — |