code: def test_clone1(model, preds_type, use_calibration, binarize_preds):
      """
      Checks if an `AttributeError` is raised because the models do NOT support `predict_proba`,
      ``use_calibration=False`` and we are interested in the probabilities due to ``binarize_preds=False``.
      """
      with pytest.raises(AttributeError):
          ClassifierDriftSklearn(
              x_ref=np.random.randn(100, 5),
              model=model,
              preds_type=preds_type,
              use_calibration=use_calibration,
              binarize_preds=binarize_preds,
          )
  
imports: import pytest
  import numpy
  from typing import Union
  from alibi_detect.cd.sklearn.classifier import ClassifierDriftSklearn
  from sklearn.svm import SVC
  from sklearn.svm import LinearSVC
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier, AdaBoostClassifier
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.gaussian_process import GaussianProcessClassifier
  from sklearn.neural_network import MLPClassifier
  from sklearn.naive_bayes import GaussianNB
  from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis
label_desc: Use image node_id 4 for calling a global function with example usage: test_clone1(model, preds_type, use_calibration, binarize_preds) without return types