code: def test_shuffle_cross_validation():
      # somewhat nonlinear design with sorted target
      rng = np.random.RandomState(42)
      X = rng.normal(size=(100, 10))
      w = rng.normal(size=(10,))
      y = np.dot(X, w)
      y = 0.1 * y**2 + 2 * y
      # throws off linear model if we sort
      sorting = np.argsort(y)
      X = pd.DataFrame(X[sorting, :])
      y = pd.Series(y[sorting])
      sr = SimpleRegressor(shuffle=False).fit(X, y)
      assert sr.log_[-2].r2 < 0.1
      sr = SimpleRegressor().fit(X, y)
      assert sr.log_[-2].r2 > 0.9
  
imports: import pytest
  import pandas
  import numpy
  from sklearn.datasets import load_iris, make_blobs, load_digits, fetch_openml
  from sklearn.svm import LinearSVC
  from sklearn.linear_model import LogisticRegression
  from sklearn.dummy import DummyClassifier
  from dabl.datasets import load_titanic
  from dabl.models import SimpleClassifier, SimpleRegressor, AnyClassifier
label_desc: Use image node_id 12 for calling a global function with example usage: test_shuffle_cross_validation() without return types