code: 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()
  
imports: from sklearn_evaluation import ClassifierEvaluator
  from sklearn import datasets
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 1 for calling a global function with example usage: test_can_plot() without return types