Network Classification on REDDIT-B
79.68F1 ScoreSGN(0,1,2)
Evaluation Results
| Method | Links | |
|---|---|---|
| SGN(0,1,2)Feature Extraction=CapsGNN2019.03 | 79.68 | |
| SGN(0,1,2)Feature Extraction=Handcraft2019.03 | 79.23 | |
| SGN(0,1)Feature Extraction=Handcraft2019.03 | 79.15 | |
| SGN(0,2)Feature Extraction=Handcraft2019.03 | 78.8 | |
| SGN(0)Feature Extraction=Handcraft2019.03 | 78.68 | |
| SGN(0,1)Feature Extraction=CapsGNN2019.03 | 78.49 | |
| SGN(0,1,2)Feature Extraction=Deep WL2019.03 | 78.41 | |
| SGN(0,2)Feature Extraction=CapsGNN2019.03 | 78.17 | |
| SGN(0,1,2)Feature Extraction=Graph2vec2019.03 | 78.04 | |
| SGN(0,1)Feature Extraction=Graph2vec2019.03 | 77.63 | |
| SGN(0,2)Feature Extraction=Graph2vec2019.03 | 77.39 | |
| SGN(0,1)Feature Extraction=Deep WL2019.03 | 77.35 | |
| SGN(0)Feature Extraction=Deep WL2019.03 | 77.25 | |
| SGN(1,2)Feature Extraction=Handcraft2019.03 | 77.23 | |
| SGN(0,1,2)Feature Extraction=WL2019.03 | 77.03 | |
| SGN(1)Feature Extraction=Deep WL2019.03 | 76.93 | |
| SGN(0,2)Feature Extraction=Deep WL2019.03 | 76.92 | |
| SGN(0,1)Feature Extraction=WL2019.03 | 76.9 | |
| SGN(1)Feature Extraction=Handcraft2019.03 | 76.5 | |
| SGN(1,2)Feature Extraction=Deep WL2019.03 | 76.2 | |
| SGN(0)Feature Extraction=CapsGNN2019.03 | 76.12 | |
| SGN(0)Feature Extraction=Graph2vec2019.03 | 76 | |
| SGN(1,2)Feature Extraction=Graph2vec2019.03 | 76 | |
| SGN(1,2)Feature Extraction=CapsGNN2019.03 | 75.73 | |
| SGN(1)Feature Extraction=CapsGNN2019.03 | 75.64 | |
| SGN(0,2)Feature Extraction=WL2019.03 | 75.4 | |
| SGN(1)Feature Extraction=Graph2vec2019.03 | 75.34 | |
| SGN(2)Feature Extraction=Deep WL2019.03 | 75.29 | |
| SGN(0)Feature Extraction=WL2019.03 | 75.15 | |
| SGN(1)Feature Extraction=WL2019.03 | 74.83 | |
| SGN(2)Feature Extraction=Graph2vec2019.03 | 74.5 | |
| SGN(2)Feature Extraction=Handcraft2019.03 | 74.37 | |
| SGN(2)Feature Extraction=WL2019.03 | 74.34 | |
| SGN(1,2)Feature Extraction=WL2019.03 | 74.15 | |
| SGN(2)Feature Extraction=CapsGNN2019.03 | 72.41 |