Bayesian Deep Learning
twiecki.github.ioVery nice article!
But ... You generated your original data from: "sklearn.datasets.make_moons". Then you say that you tested your classifier on a hold-out set with "sample_ppc()".
I don't think that's a true hold-out set. A true hold-out set would be obtained by running "make_moons()" again to generate new data.
Have you tried that? It would be interesting I think.
I'll run the test myself too ...
Again, thanks for a very nice and informative article.
Thanks for your comment! I did split the data in two, but it's easy to miss. X_test and X_train are the two sets. ann_input.set_value(X_test) then switches in the test values. That's identical to running make_moons() again.
OK, I didn't understand how the "neural_network" was connected to the data.
Thanks for responding.