class_docstr: Test ROCAUC visualizer
class_docstr_tok: ["Test","ROCAUC","visualizer"]
docstr: Test ROCAUC with a binary classifier with both decision & predict_proba
docstr_tok: ["Test","ROCAUC","with","a","binary","classifier","with","both","decision","&","predict_proba"]
code: def test_binary_probability_decision(self):
      """
      Test ROCAUC with a binary classifier with both decision & predict_proba
      """
      # Create and fit the visualizer
      visualizer = ROCAUC(AdaBoostClassifier())
      visualizer.fit(self.binary.X.train, self.binary.y.train)
  
      # Score the visualizer
      s = visualizer.score(self.binary.X.test, self.binary.y.test)
  
      # Test that score method successfully returns a value between 0 and 1
      assert 0 <= s <= 1
  
      # Check the scores
      assert_valid_rocauc_scores(visualizer)
  
      # Compare the images
      visualizer.finalize()
      self.assert_images_similar(visualizer, tol=0.1, windows_tol=10)
  
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 2 for calling the TestROCAUC obj's underlying member method code with example usage: obj.test_binary_probability_decision() without return types