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A question about negative samples generation in preprocessing.py #70
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Hi, I had the same issue. I gave it some thought, and I realized that the negative validation/training samples should be able to sample from the test's samples, otherwise the algorithm would have an edge over the test samples. In other words, edges in the test set can be sampled as negative examples in the validation/training sets (this could happen in a real world scenario). So, this explain why ismember is segregated in train_edges and val_edges. However, there is this line:
Which I don't understand the purpose of. |
I understand why
|
Hi,
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Hello, I am having the same issue. |
Hi Thomas,
I'm confused when you generate the negative edge labels of validation set as:
However, the test negative set is confirmed by
Why does validation set use
ismember([idx_j, idx_i], train_edges)
andismember([idx_i, idx_j], val_edges)
instead ofismember([idx_i, idx_j], edges_all)
?Wu Shiauthie
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