code: def test_all_params():
      data_path = pyunit_utils.locate(
          "smalldata/airlines/allyears2k_headers.zip"
      )
      df = h2o.import_file(data_path)
      params = {
          "model_id": "agg",
          "training_frame": df,
          "response_column": "IsDepDelayed",
          "ignored_columns": ["UniqueCarrier"],
          "ignore_const_cols": False,
          "target_num_exemplars": 500,
          "rel_tol_num_exemplars": 0.3,
          "transform": "standardize",
          "categorical_encoding": "eigen",
      }
      try:
          model = H2OAggregatorEstimator(**params)
          model.train(training_frame=df)
      except:
          assert False, "Should not throw error on valid parameters"
  
imports: import h2o
  from tests import pyunit_utils
  from h2o.frame import H2OFrame
  from h2o.estimators.aggregator import H2OAggregatorEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_all_params() without return types