code: def test_gaussian_result_frame_model_id():
      d = h2o.import_file(
          path=pyunit_utils.locate("smalldata/logreg/prostate.csv")
      )
      my_y = "GLEASON"
      my_x = ["AGE", "RACE", "CAPSULE", "DCAPS", "PSA", "VOL", "DPROS"]
  
      maxr_model = modelSelection(
          seed=12345, max_predictor_number=7, mode="maxr"
      )
      maxr_model.train(training_frame=d, x=my_x, y=my_y)
      verifyCorrectAddedRemovedPreds(maxr_model, "maxr")
  
      maxrsweep_model = modelSelection(
          seed=12345,
          max_predictor_number=7,
          mode="maxrsweep",
          build_glm_model=True,
      )
      maxrsweep_model.train(training_frame=d, x=my_x, y=my_y)
      verifyCorrectAddedRemovedPreds(maxrsweep_model, "maxrsweep")
  
      maxrsweep_model_glm = modelSelection(
          seed=12345, max_predictor_number=7, mode="maxrsweep"
      )
      maxrsweep_model_glm.train(training_frame=d, x=my_x, y=my_y)
      verifyCorrectAddedRemovedPreds(maxrsweep_model_glm, "maxrsweep")
  
      maxrsweep_model_MM = modelSelection(
          seed=12345,
          max_predictor_number=7,
          mode="maxrsweep",
          multinode_mode=True,
      )
      maxrsweep_model_MM.train(training_frame=d, x=my_x, y=my_y)
      verifyCorrectAddedRemovedPreds(maxrsweep_model_MM, "maxrsweep")
  
      allsubsets_model = modelSelection(
          seed=12345, max_predictor_number=7, mode="allsubsets"
      )
      allsubsets_model.train(training_frame=d, x=my_x, y=my_y)
      verifyCorrectAddedRemovedPreds(allsubsets_model, "allsubsets")
  
      backward_model = modelSelection(
          seed=12345, min_predictor_number=3, mode="backward"
      )
      backward_model.train(training_frame=d, x=my_x, y=my_y)
      verifyCorrectAddedRemovedPreds(backward_model, "backward")
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.model_selection import H2OModelSelectionEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_gaussian_result_frame_model_id() without return types