class_docstr: Test ROCAUC visualizer
class_docstr_tok: ["Test","ROCAUC","visualizer"]
docstr: Test ROCAUC to see if _binary_decision with micro = True raises an error
docstr_tok: ["Test","ROCAUC","to","see","if","_binary_decision","with","micro","=","True","raises","an","error"]
code: def test_binary_micro_error(self):
      """
      Test ROCAUC to see if _binary_decision with micro = True raises an error
      """
      # Create visualizer with a linear model to force a binary decision
      visualizer = ROCAUC(
          LinearSVC(random_state=42), micro=True, per_class=False
      )
      visualizer.fit(self.binary.X.train, self.binary.y.train)
  
      # Ensure score raises error (micro curves aren't defined for binary decisions)
      with pytest.raises(ModelError):
          visualizer.score(self.binary.X.test, self.binary.y.test)
  
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 6 for calling the TestROCAUC obj's underlying member method code with example usage: obj.test_binary_micro_error() without return types