code: def test_oob_score_regression():
      # Check that oob prediction is a good estimation of the generalization
      # error.
      rng = check_random_state(0)
      X_train, X_test, y_train, y_test = train_test_split(
          diabetes.data, diabetes.target, random_state=rng
      )
  
      clf = BaggingRegressor(
          estimator=DecisionTreeRegressor(),
          n_estimators=50,
          bootstrap=True,
          oob_score=True,
          random_state=rng,
      ).fit(X_train, y_train)
  
      test_score = clf.score(X_test, y_test)
  
      assert abs(test_score - clf.oob_score_) < 0.1
  
      # Test with few estimators
      warn_msg = (
          "Some inputs do not have OOB scores. This probably means too few "
          "estimators were used to compute any reliable oob estimates."
      )
      with pytest.warns(UserWarning, match=warn_msg):
          regr = BaggingRegressor(
              estimator=DecisionTreeRegressor(),
              n_estimators=1,
              bootstrap=True,
              oob_score=True,
              random_state=rng,
          )
          regr.fit(X_train, y_train)
  
imports: from itertools import cycle, product
  import joblib
  import numpy
  import pytest
  from sklearn.base import BaseEstimator
  from sklearn.datasets import load_diabetes, load_iris, make_hastie_10_2
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.ensemble import BaggingClassifier, BaggingRegressor, HistGradientBoostingClassifier, HistGradientBoostingRegressor
  from sklearn.feature_selection import SelectKBest
  from sklearn.linear_model import LogisticRegression, Perceptron
  from sklearn.model_selection import GridSearchCV, ParameterGrid, train_test_split
  from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import FunctionTransformer, scale
  from sklearn.random_projection import SparseRandomProjection
  from sklearn.svm import SVC, SVR
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 9 for calling a global function with example usage: test_oob_score_regression() without return types