code: def train_example_model():
      prostate_frame = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
  
      example = None
      try:
          from h2o.estimators.example import H2OExampleEstimator
  
          example = H2OExampleEstimator(max_iterations=42)
      except ImportError as error:
          print(error)
  
      if example is None:
          print(
              "This build doesn't have the example estimator built-in"
          )
          return
  
      example.train(training_frame=prostate_frame)
  
      assert example._model_json["output"]["maxs"] == [
          380.0,
          1.0,
          79.0,
          2.0,
          4.0,
          2.0,
          139.7,
          97.6,
          9.0,
      ]
  
label_desc: Use image node_id 1 for calling a global function with example usage: train_example_model() without return types