speedrf on iris, even with 40 trees, random effects mean train, then predict on train data, can still get 1 wrong
(normally it's 0 wrong). affect error rate on predict.
change the netstat in h2o_os_util to not use p
increase timeout on covtype parse for test_GLM2_poisson_1.py (busy systems)
Merge branch 'master' of github.com:0xdata/h2o