Training accuracy vs test accuracy

Question

I am training a CNN and I am getting results of 85% accuracy in the training set, and 65% accuracy in the test set.

Is it okey to assume that, with a proper setting of the regularization of the network (dropout and L2 in my case), my test accuracy should get very close to my training accuracy (which will at the same time decrease as the regularization increases) ?

So let's say for instance, a 75%-74% accuracy ?

Answer 1

With a proper setting of the regularization of all parameters of the network and with a well representative data batch, you should have a small difference between your test accuracy and your training accuracy. But of course you need to optimize your model with parameter optimization and feature selection.

Maybe you can check this link to find some more informations.

Hope it helps !