code: def get_model_gbm():
      prostate = h2o.import_file(
          path=pyunit_utils.locate("smalldata/logreg/prostate.csv")
      )
      prostate.describe()
      prostate[1] = prostate[1].asfactor()
  
      prostate_gbm = H2OGradientBoostingEstimator(
          distribution="bernoulli"
      )
      prostate_gbm.train(
          x=list(range(2, 9)), y=1, training_frame=prostate
      )
      prostate_gbm.show()
  
      prostate_gbm.predict(prostate)
      model = h2o.get_model(prostate_gbm.model_id)
      model.show()
  
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: get_model_gbm() without return types