code: def pubdev_7064():
      insurance = h2o.import_file(
          pyunit_utils.locate("smalldata/glm_test/insurance.csv")
      )
  
      predictors = insurance.columns[0:4]
      response = "Claims"
      insurance["Group"] = insurance["Group"].asfactor()
      insurance["Age"] = insurance["Age"].asfactor()
  
      insurance_gbm_exception = H2OGradientBoostingEstimator(
          distribution="huber",
          huber_alpha=0.9,
          nfolds=3,
          seed=1234,
          sample_rate=0.25,
      )
      insurance_gbm_exception.train(
          x=predictors, y=response, training_frame=insurance
      )
  
imports: import sys
  import h2o
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: pubdev_7064() without return types