Table 2 Optimal set of parameters for each node embedding method considered in the study
From: GraphTar: applying word2vec and graph neural networks to miRNA target prediction
\(E_{GNN}\) | \(L_{GNN}\) | \(D_{GNN}\) | \(L_{FC}\) | \(D_{FC}\) | \(P_h\) | \(R_{D}\) |
|---|---|---|---|---|---|---|
GCN | 3 | 128 | 2 | 512 | MAX | 0.4 |
GAT | 5 | 256 | 2 | 128 | ADD | 0.4 |
GraphSAGE | 5 | 256 | 3 | 256 | ADD | 0.4 |