Table 3 AUC for all the algorithms applied to the networks generated by the Polynomial model
From: Influence of clustering coefficient on network embedding in link prediction
| Â | Â | Algorithms | |||
|---|---|---|---|---|---|
Parameters | Common Neighbours | Matrix Factorisation | Laplacian Eigenmaps | node2vec | |
\({{\gamma = 2.25}}\) | \({{\beta = 0.00}}\) | \(0.501 \pm 0.018\) | \(\bf {0.841 \pm 0.020}\) | \(0.472 \pm 0.025\) | \(0.429 \pm 0.016\) |
\({{\beta = 0.20}}\) | \(0.561 \pm 0.021\) | \(\bf {0.835 \pm 0.013}\) | \(0.511 \pm 0.022\) | \(0.462 \pm 0.015\) | |
\({{\beta = 0.40}}\) | \(0.628 \pm 0.018\) | \(\bf {0.829 \pm 0.014}\) | \(0.565 \pm 0.023\) | \(0.511 \pm 0.018\) | |
\({{\gamma = 2.50}}\) | \({{\beta = 0.00}}\) | \(0.511 \pm 0.009\) | \(\bf {0.728 \pm 0.018}\) | \(0.487 \pm 0.018\) | \(0.452 \pm 0.018\) |
\({{\beta = 0.20}}\) | \(0.578 \pm 0.012\) | \(\bf {0.719 \pm 0.016}\) | \(0.527 \pm 0.020\) | \(0.484 \pm 0.018\) | |
\({{\beta = 0.60}}\) | \(0.699 \pm 0.013\) | \(\bf {0.719 \pm 0.032}\) | \(0.659 \pm 0.027\) | \(0.615 \pm 0.022\) | |
\({{\gamma = 3.00}}\) | \({{\beta = 0.00}}\) | \(0.502 \pm 0.005\) | \(\bf {0.615 \pm 0.018}\) | \(0.481 \pm 0.014\) | \(0.459 \pm 0.017\) |
\({{\beta = 0.20}}\) | \(0.576 \pm 0.009\) | \(\bf {0.626 \pm 0.016}\) | \(0.528 \pm 0.017\) | \(0.517 \pm 0.018\) | |
\({{\beta = 0.60}}\) | \(\bf {0.701 \pm 0.012}\) | \(0.615 \pm 0.021\) | \(0.660 \pm 0.022\) | \(0.645 \pm 0.020\) | |