class_docstr: Test ROCAUC visualizer
class_docstr_tok: ["Test","ROCAUC","visualizer"]
docstr: Test ROCAUC with a target specifying a list of classes as strings
docstr_tok: ["Test","ROCAUC","with","a","target","specifying","a","list","of","classes","as","strings"]
code: def test_rocauc_label_encoded(self):
      """
      Test ROCAUC with a target specifying a list of classes as strings
      """
      class_labels = ["a", "b", "c", "d", "e", "f"]
  
      # Create and fit the visualizer
      visualizer = ROCAUC(LogisticRegression(), classes=class_labels)
      visualizer.fit(self.multiclass.X.train, self.multiclass.y.train)
  
      # Score the visualizer
      visualizer.score(self.multiclass.X.test, self.multiclass.y.test)
      assert list(visualizer.classes_) == class_labels
  
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 16 for calling the TestROCAUC obj's underlying member method code with example usage: obj.test_rocauc_label_encoded() without return types