Fix NPE for displaying best_model.
Allow grid search models for DL to all compete for the overall best model when specifying best_model_key.
Relax assertion on accuracy for autoencoder test.
Cleanup code.
Auto-generate best_model_key for Deep Learning, in case it was not specified.
This guarantees that there's always a best model in KV-store, for checkpoint continuation.
Note, however, that the model itself remains the model that's obtained after training for N epochs.
This is needed because we don't know how good the scoring dataset (sample) is, since the user has the option
to specify a small sample of the data to be used for scoring (for speed).
Add deeplearning to the list of available RUnit test groups.
Merge branch 'master' of https://github.com/0xdata/h2o