Hi all,
I'm currently looking at the GridSearch example (
http://scikit-learn.org/0.9/auto_examples/grid_search_digits.html), and I
don't completely get the point of using cross-validation twice. Why aren't
the parameters and the classifier selected in on cross-validations step?
Furthermore, I was wondering if I do a refit at the end of the GridSearch
procedure, it will train the model on the complete dataset, so that it can
be applied on the test set afterwards?
Best and thanks,
Mathias
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