code: def grid_airlinesGBM():
      air = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/airlines/allyears2k_headers.zip"
          )
      )
      # air.summary()
      myX = ["DayofMonth", "DayOfWeek"]
  
      from h2o.estimators.gbm import H2OGradientBoostingEstimator
  
      air_grid = H2OGradientBoostingEstimator(
          ntrees=[5, 10, 15],
          learn_rate=[0.1, 0.2],
          max_depth=[2, 3, 4],
          distribution="bernoulli",
      )
      air_grid.train(x=myX, y="IsDepDelayed", training_frame=air)
      # air_grid = h2o.gbm(y=air["IsDepDelayed"], x=air[myX],
      #                distribution="bernoulli",
      #                ntrees=[5,10,15],
      #                max_depth=[2,3,4],
      #                learn_rate=[0.1,0.2])
      air_grid.show()
  
label_desc: Use image node_id 1 for calling a global function with example usage: grid_airlinesGBM() without return types