code: def isolation_forest():
      print("Isolation Forest Smoke Test")
  
      train = h2o.import_file(
          pyunit_utils.locate("smalldata/anomaly/ecg_discord_train.csv")
      )
      test = h2o.import_file(
          pyunit_utils.locate("smalldata/anomaly/ecg_discord_test.csv")
      )
  
      if_model = H2OIsolationForestEstimator(
          ntrees=7, seed=12, sample_size=5
      )
      if_model.train(training_frame=train)
  
      print(if_model)
  
      perf = if_model.model_performance()
      print(perf)
      assert perf.mean_score() > 0
      assert perf.mean_normalized_score() > 0
  
      test_pred = if_model.predict(test)
      assert test_pred.nrow == 23
  
imports: import sys, os
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.isolation_forest import H2OIsolationForestEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: isolation_forest() without return types