code: def test_4659():
      train_h2o = h2o.import_file(
          pyunit_utils.locate("smalldata/logreg/prostate_train.csv")
      )
      test_h2o = h2o.import_file(
          pyunit_utils.locate("smalldata/logreg/prostate_test.csv")
      )
  
      # remove response column
      test_h2o = test_h2o[:, 2:]
  
      h2o_glm = H2OGeneralizedLinearEstimator()
      h2o_glm.train(training_frame=train_h2o, x=[2, 3, 4, 5, 6, 7], y=1)
  
      h2o_glm_predictions = h2o_glm.predict(
          test_data=test_h2o
      ).as_data_frame()
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_4659() without return types