code: def test_regressor():
      X, y = boston_housing_data()
      reg1 = Lasso(random_state=1)
      reg2 = Ridge(random_state=1)
  
      X_train, X_test, y_train, y_test = train_test_split(
          X, y, test_size=0.25, random_state=123
      )
  
      score1 = reg1.fit(X_train, y_train).score(X_test, y_test)
      score2 = reg2.fit(X_train, y_train).score(X_test, y_test)
  
      assert round(score1, 2) == 0.66, score1
      assert round(score2, 2) == 0.68, score2
  
      t, p = paired_ttest_resampled(
          estimator1=reg1, estimator2=reg2, X=X, y=y, random_seed=1
      )
  
      assert round(t, 3) == -7.697, t
      assert round(p, 3) == 0.000, p
  
file_path: mlxtend/mlxtend/evaluate/tests/test_paired_ttest_resampled.py
imports: import sys
  from packaging.version import Version
  from sklearn import __version__
  from sklearn.linear_model import Lasso, LogisticRegression, Ridge
  from sklearn.model_selection import train_test_split
  from sklearn.tree import DecisionTreeClassifier
  from mlxtend.data import boston_housing_data, iris_data
  from mlxtend.evaluate import paired_ttest_resampled
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 4 for calling a global function with example usage: test_regressor() without return types