code: def test_rf_oob(
      model,
      p_val,
      n,
      n_features,
      n_folds,
      preds_type,
      binarize_preds,
      use_calibration,
      use_oob,
  ):
      """
      Checks if all valid combination of `binarize_preds`, `use_calibration` and `use_oob` when ``preds_type='probs'``
      are working properly.
      """
      np.random.seed(0)
  
      x_ref = np.random.randn(n, n_features)
      x_test0 = np.random.randn(n, n_features)
      x_test1 = np.random.randn(n, n_features) + 1
      cd = ClassifierDriftSklearn(
          x_ref=x_ref,
          preds_type=preds_type,
          model=model,
          p_val=p_val,
          n_folds=n_folds,
          binarize_preds=binarize_preds,
          use_calibration=use_calibration,
          use_oob=use_oob,
      )
  
      preds_0 = cd.predict(x_test0)
      assert cd.n == len(x_test0) + len(x_ref)
      assert preds_0["data"]["is_drift"] == 0
      assert preds_0["data"]["distance"] >= 0
  
      preds_1 = cd.predict(x_test1)
      assert cd.n == len(x_test1) + len(x_test0) + len(x_ref)
      assert preds_1["data"]["is_drift"] == 1
      assert preds_1["data"]["distance"] >= 0
  
      assert preds_0["data"]["distance"] < preds_1["data"]["distance"]
      assert cd.meta["params"]["preds_type"] == preds_type
      assert cd.meta["params"]["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 11 for calling a global function with example usage: test_rf_oob(model, p_val, n, n_features, n_folds, preds_type, binarize_preds, use_calibration, use_oob) without return types