Disallow saving to the best_model when n_folds != 0, since we only score at the very end.
Add new option to Deep Learning: override_with_best_model (defaults to true), to replace the final
model weights/biases with the ones from the best model found so far (as judged by the scoring,
which of course depends on the scoring dataset).  This makes it easier for R users to get the best models.
Web GUI users already had the option to check out the best model via the provided link.
Add new option override_with_best_model to R docs.
Allow class balance options without expert_mode.
Add test for override_with_best_model.
Remove best_model_key from the user-given parameters, and make internal user-hidden key.
Still display that best_model key in the JSON under actual_best_model and on the web GUI as "go to best model".
Modify tests.
Update R docs, and DL vignette.
Update DL JUnit test for imbalance, use model that generalizes better.
Merge branch 'master' of https://github.com/0xdata/h2o
Allow continuation of the best model so far (when it's not copied over to the main model).
Merge branch 'master' of https://github.com/0xdata/h2o into spence-newR
update h2o-DESCRIPTION to have models.R reference