code: def vi_reg():
      data = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/gbm_test/BostonHousing.csv"
          )
      )
      # data.summary()
  
      rf = H2ORandomForestEstimator(
          ntrees=100, max_depth=20, nbins=100, seed=0
      )
      rf.train(x=list(range(13)), y=13, training_frame=data)
  
      ranking = [
          rf._model_json["output"]["variable_importances"].cell_values[
              v
          ][0]
          for v in range(data.ncol - 1)
      ]
      print(ranking)
      assert tuple([ranking[0], ranking[1]]) == tuple(
          ["rm", "lstat"]
      ), "expected specific variable importance ranking"
  
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.random_forest import H2ORandomForestEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: vi_reg() without return types