I followed Stochastic Training of GNN for Link Prediction tutorial to build my link prediction model, however, this tutorial evaluates model performance on node classification task. I am wondering how to evaluate my model performance on link prediction task.
There are generally two approaches depending on your use cases: one that cares of AUC and another that cares of ranking. Either way, for each positive edge you will have a set of negative edges to compare against.
Taking AUC as an example, typically you will have a set of test positive edges and a set of test negative edges, and you evaluate it like a normal binary classification model.
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