code: def test_two_classes(ploomber_value_error_message):
      np.random.seed(0)
      X, y = load_iris(return_X_y=True)
      clf = LogisticRegression()
      clf.fit(X, y)
      probas = clf.predict_proba(X)
      with pytest.raises(
          ValueError, match=ploomber_value_error_message
      ) as e:
          ks_statistic(y, probas)
      assert (
          "Cannot calculate KS statistic for data with 3 category/ies"
          in str(e.value)
      )
  
file_path: sklearn-evaluation/tests/test_ks_statistic.py
imports: import numpy
  import pytest
  import matplotlib.pyplot
  from matplotlib.testing.decorators import image_comparison
  from sklearn.linear_model import LogisticRegression
  from sklearn.datasets import load_breast_cancer, load_iris
  from sklearn_evaluation.plot import ks_statistic
label_desc: Use image node_id 3 for calling a global function with example usage: test_two_classes(ploomber_value_error_message) without return types