Generates comments including column name for each model col domain.
Fix in tests for javaprediction.

- incorrect handling of header (header was not properly skipped)
- incorrect handling of NAs
- minor code polishment
Proper handling of NaN in scoring.

Now generated code and interpreter match during handling NaN during
prediction.
Increase the relative error tolerance for the NN_mnist test case on multi-VM to
10%. Note: this is needed because only 1 node contributes (each mode is running
in multi-threaded single-node mode), and doesn't get to see all the training
data. Expect this test to be tightened as soon as the distributed version is
ready.
Merge branch 'master' of github.com:0xdata/h2o
Report proper NaN if mapping for a given enum-value is not found.
Fixed a bug in passing class weights to RF1
Use a local single-VM threaded trainer for Mnist example.
Fix for PUB-112. Forgot to subtract 1 to get null degrees of freedom
Dropped col.names parameter by accident
Add scatter plot of the two_spiral dataset for illustration.
Speed up NN with tanh by not calling tanh(x), but an identical expression
containing only exp(x).

This speeds up a single-layer NN using tanh by 33%.
Remove all matching H2O keys before importing.

Change "import folder" to "sync folder".  Remove all keys with
file-prefix names matching the folder, before importing.  This will
force a re-load of data in the same directory - so if you've removed a
junk file from a directory & re-import, you'll have keys that exactly
match the directory.  Ditto for editing a file & re-importing.
Merge branch 'master' of https://github.com/0xdata/h2o
Add the "Two Spirals" test for Neural Networks back.  Use parameters that lead
to fast convergence (about 10 seconds on a laptop), and test that we achieve 0%
training error.  Also only run this during nightly testing, not from
JUnitRunner, since we already have the Iris test there.
Change some default arguments for NN to something that might generalize better.
Make test_junit.py run from inside the h2o/py directory.
Basic resource check on parsing large files

Toss an IAE if the dataset on disk is >2x cluster memory (Parse1) or >
4x cluster memory (Parse2).  Fix for PUB-95
Merge branch 'arno-deeplearning'
Minor fixes in DTree java code generator.