code: from sklearn_evaluation import ClassifierEvaluator
  
  # import matplotlib.pyplot as plt
  from sklearn import datasets
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import train_test_split
  
  
  def test_can_plot():
      data = datasets.make_classification(200,
                                          10,
                                          n_informative=5,
                                          class_sep=0.65)
      X = data[0]
      y = data[1]
  
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)
  
      est = RandomForestClassifier()
      est.fit(X_train, y_train)
  
      evaluator = ClassifierEvaluator(est, y_true=y_test, X=X_test)
  
      evaluator.confusion_matrix()
  
apis: sklearn.ensemble.RandomForestClassifier sklearn.model_selection.train_test_split sklearn.datasets.make_classification