class_docstr: Test ClassPredictionError visualizer
class_docstr_tok: ["Test","ClassPredictionError","visualizer"]
docstr: Test class must be either binary or multiclass type
docstr_tok: ["Test","class","must","be","either","binary","or","multiclass","type"]
code: def test_class_type(self):
      """
      Test class must be either binary or multiclass type
      """
      X, y = make_multilabel_classification()
      model = RandomForestClassifier()
      model.fit(X, y)
      with pytest.raises(YellowbrickValueError):
          visualizer = ClassPredictionError(model)
          visualizer.score(X, y)
  
imports: import pytest
  import matplotlib.pyplot
  from yellowbrick.exceptions import ModelError
  from yellowbrick.datasets import load_occupancy
  from yellowbrick.classifier.class_prediction_error import *
  from sklearn.svm import LinearSVC, SVC
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.datasets import make_multilabel_classification
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import MinMaxScaler
  from unittest.mock import patch
  from tests.base import VisualTestCase
label_desc: Use image node_id 9 for calling the TestClassPredictionError obj's underlying member method code with example usage: obj.test_class_type() without return types