Could you please tell me how to conduct cross-validation with different splits?
I noticed in the GCN paper that the authors conducted a 5-fold cross-validation experiment with 5 different train/test split.
However, the train/validation/test split provided by DGL seems to be fixed. So do we need to split the datasets manually if we want to conduct the cross-validation, or can this be simply achieved by DGL?
If we need to manually achieve this, could you please tell me how the datasets should be split? I did not find any detail in the paper, eg. how many train/test points in total, how many train/test points per category, etc.
Thank you very much!