Diagnostics for Classification&Regression

Currently, the attained objective function is not computed (for efficiency reasons, as one evaluation requires one full pass through the data).

For diagnostics and comparing different algorithms, we should however provide this as a separate function (one MR).

Doing this requires the loss and regularizer functions themselves, not only their gradients (which are currently in the Gradient class). How about adding the new function directly on the corresponding models in classification/* and regression/* ? Any thoughts?