code: def test_make_leaderboard_unsupervised():
      train = h2o.upload_file(
          pyunit_utils.locate("smalldata/titanic/titanic_expanded.csv")
      )
      train["name"] = train["name"].asfactor()
  
      pca = H2OPrincipalComponentAnalysisEstimator()
      pca.train(training_frame=train)
  
      kmeans = H2OKMeansEstimator(k=5)
      kmeans.train(training_frame=train)
  
      try:
          print(h2o.make_leaderboard([pca, kmeans]))
          assert (
              False
          ), "Should have failed - no support for unsupervised models"
      except h2o.exceptions.H2OServerError:
          pass
  
file_path: h2o-3/h2o-py/tests/testdir_misc/explain/pyunit_make_leaderboard.py
imports: import os
  import sys
  import h2o
  import h2o.exceptions
  from tests import pyunit_utils, dataset_prostate, CustomMaeFunc
  from h2o.automl import H2OAutoML
  from h2o.estimators import *
  from h2o.grid import H2OGridSearch
label_desc: Use image node_id 4 for calling a global function with example usage: test_make_leaderboard_unsupervised() without return types