class_docstr: Test ClassPredictionError visualizer
class_docstr_tok: ["Test","ClassPredictionError","visualizer"]
docstr: Test that visualizer can be accessed within a sklearn pipeline
docstr_tok: ["Test","that","visualizer","can","be","accessed","within","a","sklearn","pipeline"]
code: def test_within_pipeline(self):
      """
      Test that visualizer can be accessed within a sklearn pipeline
      """
      X, y = load_occupancy(return_dataset=True).to_pandas()
      classes = ["unoccupied", "occupied"]
  
      X_train, X_test, y_train, y_test = tts(
          X, y, test_size=0.2, shuffle=True, random_state=42
      )
  
      model = Pipeline(
          [
              ("minmax", MinMaxScaler()),
              (
                  "cpe",
                  ClassPredictionError(
                      SVC(random_state=42), classes=classes
                  ),
              ),
          ]
      )
  
      model.fit(X_train, y_train)
      model.score(X_test, y_test)
      model["cpe"].finalize()
      self.assert_images_similar(
          model["cpe"], tol=12.5, windows_tol=13.3
      )
  
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 12 for calling the TestClassPredictionError obj's underlying member method code with example usage: obj.test_within_pipeline() without return types