code: def ecologyGBM_random_noise():
      ecology_train = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/gbm_test/ecology_model.csv"
          )
      )
      gbm_h2o = H2OGradientBoostingEstimator(pred_noise_bandwidth=0.5)
      gbm_h2o.train(
          x=list(range(2, ecology_train.ncol)),
          y="Angaus",
          training_frame=ecology_train,
      )
      print(gbm_h2o)
  
file_path: h2o-3/h2o-py/tests/testdir_algos/gbm/pyunit_ecology_gbm_random_noise.py
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  import numpy
  from sklearn import ensemble
  from sklearn.metrics import roc_auc_score
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: ecologyGBM_random_noise() without return types