You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi
I want to split a heterogeneous graph into train, dev, and test set for link_pred, but I need to have the positive and negative instances of the edges/links from a specific edge_type. Predicting that kind of edge is the problem description, other edges are just informative. Is there a way to do that with split?
Thanks,
Soha
The text was updated successfully, but these errors were encountered:
I might be wrong but I think deepsnap’s splitting functionality will give you positive and negative supervision edges for all edge types in a hetero graph. If you want to specify one edge type for your supervision edges maybe have a look at pytorch-geometric’s RandomLinkSplit, see for example how it’s used here. In the same folder there is also a hetero_link_pred example which I contributed, so I hope it doesn’t seem like showing off that I share it😅, it just seems fairly relevant to what you’re trying to do.
Hi
I want to split a heterogeneous graph into train, dev, and test set for link_pred, but I need to have the positive and negative instances of the edges/links from a specific edge_type. Predicting that kind of edge is the problem description, other edges are just informative. Is there a way to do that with split?
Thanks,
Soha
The text was updated successfully, but these errors were encountered: