Table 9 Accuracy (mean and standard deviation over 10 runs) obtained by initializing the entity features with mixed distributions
From: Graph convolutional and attention models for entity classification in multilayer networks
Network | ML-GAT | ML-GCN | GAT | GCN |
|---|---|---|---|---|
Balance | \(0.8377 \pm 0.0567\) | \(\mathbf {0.9053 \pm 0.0168}\) | \(0.6362 \pm 0.0346\) | \(0.6714 \pm 0.0489\) |
CKM-Social | \(0.9473 \pm 0.0231\) | \(0.8066 \pm 0.0399\) | \(\mathbf {0.9962 \pm 0.0069}\) | \(0.9786 \pm 0.0075\) |
Congress | \(0.8900 \pm 0.1294\) | \(\mathbf {0.9468 \pm 0.0165}\) | \(0.5458 \pm 0.1108\) | \(0.6146 \pm 0.0000\) |
DKPol | \(0.7935 \pm 0.0245\) | \(\mathbf {0.8205 \pm 0.0323}\) | \(0.7956 \pm 0.0646\) | \(0.7919 \pm 0.0424\) |
Leskovec-Ng | \(0.9944 \pm 0.0085\) | \(0.9208 \pm 0.0297\) | \(\mathbf {0.9951 \pm 0.0087}\) | \(0.9861 \pm 0.0131\) |
Starwars | \(0.7435 \pm 0.0438\) | \(0.7217 \pm 0.0625\) | \(\mathbf {0.7782 \pm 0.0493}\) | \(0.7202 \pm 0.0552\) |
Terrorist-Noordin | \(0.7133 \pm 0.0680\) | \(\mathbf {0.7550 \pm 0.0643}\) | \(0.7017 \pm 0.0337\) | \(0.6983 \pm 0.0569\) |
Terrorist-status | \(0.4883 \pm 0.0629\) | \(0.4700 \pm 0.1018\) | \(\mathbf {0.5417 \pm 0.0568}\) | \(0.5183 \pm 0.0678\) |
Vickers | \(\mathbf {0.9773 \pm 0.0321}\) | \(0.9636 \pm 0.0469\) | \(0.7727 \pm 0.1071\) | \(0.8590 \pm 0.0452\) |
Koumbia-2-mpx | \(0.7162 \pm 0.0395\) | \(\mathbf {0.7634 \pm 0.0092}\) | \(0.7006 \pm 0.0171\) | \(0.7020 \pm 0.0200\) |
Koumbia-5-mpx | \(\mathbf {0.8497 \pm 0.0092}\) | \(0.8046 \pm 0.0212\) | \(0.7759 \pm 0.0301\) | \(0.7702 \pm 0.0143\) |
Koumbia-10-mpx | \(\mathbf {0.8579 \pm 0.0148}\) | \(0.8228 \pm 0.0159\) | \(0.8361 \pm 0.0123\) | \(0.8052 \pm 0.0110\) |
Koumbia-15-mpx | \(\mathbf {0.8551 \pm 0.0075}\) | \(0.8223 \pm 0.0105\) | \(0.8539 \pm 0.0053\) | \(0.8181 \pm 0.0121\) |
Koumbia-20-mpx | \(\mathbf {0.8561 \pm 0.0157}\) | \(0.8305 \pm 0.0053\) | \(0.8549 \pm 0.0155\) | \(0.8312 \pm 0.0125\) |