class_docstr: ClassificationReport visualizer tests
class_docstr_tok: ["ClassificationReport","visualizer","tests"]
docstr: Correctly removes the colorbar for binary classification with LinearSVC
docstr_tok: ["Correctly","removes","the","colorbar","for","binary","classification","with","LinearSVC"]
code: def test_remove_color_bar(self):
      """
      Correctly removes the colorbar for binary classification with LinearSVC
      """
      _, ax = plt.subplots()
  
      viz = ClassificationReport(
          LinearSVC(random_state=42), ax=ax, colorbar=False
      )
      viz.fit(self.binary.X.train, self.binary.y.train)
      viz.score(self.binary.X.test, self.binary.y.test)
  
      self.assert_images_similar(viz, tol=40)
  
imports: import sys
  import pytest
  import yellowbrick
  import matplotlib.pyplot
  from yellowbrick.datasets import load_occupancy
  from yellowbrick.classifier.classification_report import *
  from pytest import approx
  from unittest.mock import patch
  from tests.base import VisualTestCase
  from sklearn.svm import LinearSVC, SVC
  from sklearn.naive_bayes import GaussianNB
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.datasets import make_classification
  from sklearn.model_selection import train_test_split
  from sklearn.linear_model import LassoCV, LogisticRegression
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import MinMaxScaler
label_desc: Use image node_id 12 for calling the TestClassificationReport obj's underlying member method code with example usage: obj.test_remove_color_bar() without return types