Table 12 Performance of ML-GCN over the Koumbia multilayer networks with varying number of layers, and different types of input features
From: Graph convolutional and attention models for entity classification in multilayer networks
\(\ell\) | Koumbia-Fon | Koumbia-Foff | Koumbia-normal | |||
|---|---|---|---|---|---|---|
Accuracy | MRR | Accuracy | MRR | Accuracy | MRR | |
2 | \(\mathbf {0.8520 \pm 0.0863}\) | \(\mathbf {0.9260 \pm 0.0431}\) | \(0.7444 \pm 0.0172\) | \(0.8722 \pm 0.0086\) | \(0.7503 \pm 0.0186\) | \(0.8751 \pm 0.0093\) |
5 | \(\mathbf {0.9370 \pm 0.0063}\) | \(\mathbf {0.9685 \pm 0.0032}\) | \(0.6880 \pm 0.0273\) | \(0.8411 \pm 0.0136\) | \(0.8163 \pm 0.0143\) | \(0.9082 \pm 0.0071\) |
10 | \(\mathbf {0.9359 \pm 0.0085}\) | \(\mathbf {0.9679 \pm 0.0043}\) | \(0.6540 \pm 0.0200\) | \(0.8270 \pm 0.0100\) | \(0.8237 \pm 0.0157\) | \(0.9118 \pm 0.0082\) |
15 | \(\mathbf {0.9358 \pm 0.0089}\) | \(\mathbf {0.9679 \pm 0.0044}\) | \(0.6378 \pm 0.0215\) | \(0.8189 \pm 0.0108\) | \(0.8238 \pm 0.0216\) | \(0.9119 \pm 0.0108\) |
20 | \(\mathbf {0.9363 \pm 0.0067}\) | \(\mathbf {0.9681 \pm 0.0033}\) | \(0.6282 \pm 0.0116\) | \(0.8141 \pm 0.0058\) | \(0.8221 \pm 0.0153\) | \(0.9111 \pm 0.0077\) |