code: def test_raises_error():
      # generate random data for illustrative example
      np.random.seed(42)
      x = np.random.normal(0, 1, 100)
      y = 1 + x + np.random.normal(0, 0.2, 100)
      for i in [20, 25, 50, 80]:
          y[i] += 2
      X = pd.DataFrame({"x": x, "y": y})
  
      with pytest.raises(ValueError):
          mod = RegressionOutlierDetector(
              LogisticRegression(), column="y"
          )
          mod.fit(X)
  
file_path: scikit-lego/tests/test_meta/test_regression_outlier.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.linear_model import LinearRegression, LogisticRegression
  from sklego.common import flatten
  from sklego.meta import RegressionOutlierDetector
  from tests.conftest import general_checks, outlier_checks, select_tests
label_desc: Use image node_id 4 for calling a global function with example usage: test_raises_error() without return types