code: def test_run_classification_experiment(tmp_path):
      """Test running and saving results for classifiers.
  
      Currently it just checks the files have been created, then deletes them.
      """
      dataset = "UnitTest"
      train_X, train_Y = load_unit_test("TRAIN")
      test_X, test_Y = load_unit_test("TEST")
      run_classification_experiment(
          train_X,
          train_Y,
          test_X,
          test_Y,
          TimeSeriesForestClassifier(n_estimators=10),
          str(tmp_path),
          cls_name="TSF",
          dataset="UnitTest",
          resample_id=0,
          train_file=True,
      )
      test_path = tmp_path.joinpath(
          f"TSF/Predictions/{dataset}/testResample0.csv"
      )
      train_path = tmp_path.joinpath(
          f"TSF/Predictions/{dataset}/trainResample0.csv"
      )
      assert test_path.is_file()
      assert train_path.is_file()
      # remove files
      test_path.unlink()
      train_path.unlink()
  
imports: import pytest
  from sktime.benchmarking.experiments import run_classification_experiment, run_clustering_experiment
  from sktime.classification.interval_based import TimeSeriesForestClassifier
  from sktime.clustering.k_means import TimeSeriesKMeans
  from sktime.datasets import load_unit_test
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 2 for calling a global function with example usage: test_run_classification_experiment(tmp_path) without return types