COnfusion matrix improvement
 - alignment of model and data classes for enum predictors and integer
   predictors
 - basic test cases
Model v. validation data - classes alignment integrated into UI.
Shortcut to use dataset for scoring with help of RF.
Test added into junit.py
Improvements in RF view:
 - hidden oobee option
 - number of trees is checked and respect number of trees stored in
   model
Minor UI fix in upload page.
UI fix.
Temporary RF refactoring commit.
A dedicated RFscore page. Serves as a "redirect" to RFView
Blocking on future returned by DRF corrected.
 - now it blocks correctly for all nodes to finish their DRF round
 - jobs partially refactored. Waiting for new Jobs API
No more active waiting in tests !!!
Minor refactoring in RF API.
Jobs progress disable for now - waiting for new Jobs API.
Unnecessary cast removed.
playing with 1/2 sized chunks. small tests run, this case failed in
test.py and broke it out as separate test. I hardwired the chunk size
locally like this in ValueArray.java:
-  public static final int LOG_CHK = 20; // Chunks are 1<<20, or 1Meg
+  public static final int LOG_CHK = 10; // Chunks are 1<<20, or 1Meg
   public static final long CHUNK_SZ = 1L << LOG_CHK;

failure seems simple, complains about dataset format. normally runs
fine.
Minor clean-up.
Merge branch 'master' of github.com:0xdata/h2o
Kaggle dataset contains a predictor in the 2nd column.
typo on name of the cnt that was trying to make sure we got the multiple NOPTask assertion messages out of the stdout/stderr (test_poisson_covtype20x_hosts.py tiggered in jenkins now that michal has covtype20x file there for import folder use)
can't use out_of_bag_error_estimate=1 on rf scoring (random_forest_view only)
change timeouts to be approx 2x my laptop execution time (for EC2)