Hi,
i see that one single training instance is used for regularization twice,
first in train:
// push coefficients back to zero based on the prior
regularize(instance);
and then inside the gradient implementaton for classifying the instance
with the current model:
// what does the current model say?
Vector v = classifier.classify(instance);
which then calls
@Override
public Vector classifyNoLink(Vector instance) {
// apply pending regularization to whichever coefficients matter
regularize(instance);
since there is no seal() or unseal() call the regularization is applied to
times, right? Is this planned?
Cheers,
Johannes
