Hi, I am in the process of splitting my graph into train, val, test for link prediction. My model is a GCN…

Let’s suppose I have 100 edges in a heterograph, and I set that 10 are for validation and 10 for test, which means that my training graph has 80 remaining edges.

How do I train with these 80?

- Do I remove, for example, 30 of them, and train on a graph with 50 edges, learning to predict the other 30 (+ negative examples)?
- Or do I train with the 80 edges and predict the 80 edges (+ negative examples), but risk teaching the model to memorize, instead of learning?

Thanks in advance!