class_docstr: Test ROCAUC visualizer
class_docstr_tok: ["Test","ROCAUC","visualizer"]
docstr: Test ROCAUC with classifiers that utilize predict_proba
docstr_tok: ["Test","ROCAUC","with","classifiers","that","utilize","predict_proba"]
code: def test_predict_proba_rocauc(self):
      """
      Test ROCAUC with classifiers that utilize predict_proba
      """
      # Load the model and assert there is no decision_function method.
      model = GaussianNB()
      with pytest.raises(AttributeError):
          model.decision_function
  
      # Fit model and visualizer
      visualizer = ROCAUC(model)
      visualizer.fit(self.binary.X.train, self.binary.y.train)
  
      # First 10 expected arrays in the y_scores
      first_ten_expected = np.asarray(
          [
              [0.595, 0.405],
              [0.161, 0.839],
              [0.990, 0.010],
              [0.833, 0.167],
              [0.766, 0.234],
              [0.996, 0.004],
              [0.592, 0.408],
              [0.007, 0.993],
              [0.035, 0.965],
              [0.764, 0.236],
          ]
      )
  
      # Get the predict_proba scores and evaluate
      y_scores = visualizer._get_y_scores(self.binary.X.train)
  
      # Check to see if the first 10 y_score arrays match the expected
      npt.assert_array_almost_equal(
          y_scores[:10], first_ten_expected, decimal=1
      )
  
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 21 for calling the TestROCAUC obj's underlying member method code with example usage: obj.test_predict_proba_rocauc() without return types