class_docstr: Test ROCAUC visualizer
class_docstr_tok: ["Test","ROCAUC","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()),
              (
                  "matrix",
                  ROCAUC(
                      SVC(random_state=42), classes=classes, binary=True
                  ),
              ),
          ]
      )
  
      model.fit(X_train, y_train)
      model.score(X_test, y_test)
      model["matrix"].finalize()
      self.assert_images_similar(model["matrix"], tol=12)
  
imports: import pytest
  import numpy
  import numpy.testing
  from unittest.mock import patch
  from tests.base import VisualTestCase
  from yellowbrick.classifier.rocauc import *
  from yellowbrick.exceptions import ModelError
  from yellowbrick.datasets import load_occupancy
  from sklearn.svm import LinearSVC, SVC
  from sklearn.naive_bayes import GaussianNB
  from sklearn.linear_model import LogisticRegression
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.model_selection import train_test_split
  from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier
  from sklearn.preprocessing import MinMaxScaler
  from sklearn.pipeline import Pipeline
label_desc: Use image node_id 25 for calling the TestROCAUC obj's underlying member method code with example usage: obj.test_within_pipeline() without return types