code: def test_estimator():
      data = init_data()
      raised = False
      try:
          estimator_xgb = H2OXGBoostEstimator(
              col_sample_rate_change_per_level=0.9, seed=1234
          )
          estimator_xgb.train(
              x=data["predictors"],
              y=data["response"],
              training_frame=data["train"],
              validation_frame=data["test"],
          )
      except TypeError as e:
          raised = True
          assert (
              "unexpected keyword argument 'col_sample_rate_change_per_level'"
              in str(e)
          )
  
      assert (
          raised
      ), "H2O should throw an exception if unknown parameter is passed to XGBoostEstimator!"
  
imports: import h2o
  from tests import pyunit_utils
  from h2o.estimators.xgboost import H2OXGBoostEstimator
  from h2o.exceptions import H2OResponseError, H2OValueError
  from h2o.grid.grid_search import H2OGridSearch
label_desc: Use image node_id 3 for calling a global function with example usage: test_estimator() without return types