code: def test_zero_inflated_example():
      from sklearn.model_selection import cross_val_score
  
      np.random.seed(0)
      X = np.random.randn(10000, 4)
      y = ((X[:, 0] > 0) & (X[:, 1] > 0)) * np.abs(
          X[:, 2] * X[:, 3] ** 2
      )  # many zeroes here, in about 75% of the cases.
  
      zir = ZeroInflatedRegressor(
          classifier=ExtraTreesClassifier(random_state=0),
          regressor=ExtraTreesRegressor(random_state=0),
      )
  
      zir_score = cross_val_score(zir, X, y).mean()
      et_score = cross_val_score(ExtraTreesRegressor(), X, y).mean()
  
      assert zir_score > 0.85
      assert zir_score > et_score
  
file_path: scikit-lego/tests/test_meta/test_zero_inflated_regressor.py
imports: import numpy
  import pytest
  from sklearn.ensemble import ExtraTreesClassifier, ExtraTreesRegressor
  from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor
  from sklego.common import flatten
  from sklego.meta import ZeroInflatedRegressor
  from sklego.testing import check_shape_remains_same_regressor
  from tests.conftest import general_checks, regressor_checks, select_tests
label_desc: Use image node_id 3 for calling a global function with example usage: test_zero_inflated_example() without return types