Increase tolerance to 30%. Needs revisit: It's questionable whether the
dataset/parameter combination is good for this test.
HEX-1860: Improve handling of categorical missing values.

Handling of missing categorical values in DeepLearning:

Training:
Missing categoricals turn into a new factor levels.

Testing:
If missing categorical factors are observed during training, then any unknown
categorical level during testing (either a new level or missing) will turn into
this extra missing factor.

If no missing categorical factors are seen during training AND the model
was trained with use_all_factor_levels = true, then we leave all categorical
inputs at 0 if an unknown (or missing) categorical level is seen on a test
point. If use_all_factor_levels was false during training, then we abort
with an exception, as there's nothing that can be done.
Merge branch 'master' of https://github.com/0xdata/h2o