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Not sure, to be honest. It may allow us to swap in more easily a train_test_split function passed as a parameter to NeuralNet, one that equally takes a eval_size argument. I remember we discussed being able to pass train_test_split in as a component similar to batch_iterator_train. Though it's more of a guess right now that these three arguments (X, y, eval_size) would be an appropriate interface to such a component.
Any reason the signature for
train_test_split
takes in theeval_size
rather than just reasonself. eval_size
?nolearn/nolearn/lasagne.py
Line 361 in 12f263c
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