temp checkin
add Exec Quantile
R DRF-test for binary classifier.
On the way to fix PUB-65, PUB-66: wrong comparision in generated code.

Generated code was comparing double with float, interpreter was
comparing float with float. It led to different behaviour in a few
cases.

E.g. double d = 1.98f
 ( ( (float) d) < 1.98f ) != (d < 1.98f) )
quantile added
Merge branch 'master' of github.com:0xdata/h2o
Added thresholds option to GLM1
Fixed the size of generated Forest.

Limit for a number of trees generated in the scope of
one forest. Since the Forest is represented by a class, then
we need to be careful not to polute constant pool of the class.
Fix for prediction on large trees.

Missing conversion to float caused differences between interpreted
and generated version of trees.

Moreover, I there are now 2 GBM tests generating 5000 trees and
verifying that the generated model can be compiled.
However, there are not passing now because on a small difference
on 7th decimal digit which needs to be tracked.
Fix for HEX-1470. quantile now supports arbitrary probability cutoffs
Fix for HEX-1470. Import quantiles with as.data.frame instead of through Inspect json
Merge branch 'master' into arno-deeplearning