text: from builtins import range
  import sys
  sys.path.insert(1,"../../../")
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
  
  def min_split_improvement():
  
    train  = h2o.upload_file(pyunit_utils.locate("smalldata/covtype/covtype.20k.data"))
    train["C55"] = train["C55"].asfactor()
  
    hh1 = H2OGradientBoostingEstimator(ntrees=20, min_split_improvement=0)
    hh2 = H2OGradientBoostingEstimator(ntrees=20, min_split_improvement=1e-1)
  
    hh1.train(x=list(range(55)), y="C55", training_frame=train)
    hh2.train(x=list(range(55)), y="C55", training_frame=train)
  
    assert hh1.logloss() < hh2.logloss(), "Expected logloss to get worse with large min_split_improvement"
  
  
  if __name__ == "__main__":
    pyunit_utils.standalone_test(min_split_improvement)
  else:
    min_split_improvement()
  