code: def test_sklearnex_import_rf_regression(dataframe, queue):
      from sklearnex.ensemble import RandomForestRegressor
  
      X, y = make_regression(
          n_features=4, n_informative=2, random_state=0, shuffle=False
      )
      X = _convert_to_dataframe(
          X, sycl_queue=queue, target_df=dataframe
      )
      y = _convert_to_dataframe(
          y, sycl_queue=queue, target_df=dataframe
      )
      rf = RandomForestRegressor(max_depth=2, random_state=0).fit(X, y)
      assert "sklearnex" in rf.__module__
      pred = _as_numpy(rf.predict([[0, 0, 0, 0]]))
      if daal_check_version((2024, "P", 0)):
          assert_allclose([-6.971], pred, atol=1e-2)
      else:
          assert_allclose([-6.839], pred, atol=1e-2)
  
file_path: scikit-learn-intelex/sklearnex/ensemble/tests/test_forest.py
imports: import pytest
  from numpy.testing import assert_allclose
  from sklearn.datasets import make_classification, make_regression
  from daal4py.sklearn._utils import daal_check_version
  from onedal.tests.utils._dataframes_support import _as_numpy, _convert_to_dataframe, get_dataframes_and_queues
label_desc: Use image node_id 2 for calling a global function with example usage: test_sklearnex_import_rf_regression(dataframe, queue) without return types