class_docstr: DiscriminationThreshold visualizer tests
class_docstr_tok: ["DiscriminationThreshold","visualizer","tests"]
docstr: Test for thresholdviz quick method with random dataset
code: def test_quick_method(self):
      """
      Test for thresholdviz quick method with random dataset
      """
  
      X, y = make_classification(
          n_samples=400,
          n_features=20,
          n_informative=8,
          n_redundant=8,
          n_classes=2,
          n_clusters_per_class=4,
          random_state=2721,
      )
  
      _, ax = plt.subplots()
  
      discrimination_threshold(
          BernoulliNB(), X, y, ax=ax, random_state=5, show=False
      )
      self.assert_images_similar(ax=ax, tol=10)
  
imports: import sys
  import pytest
  import yellowbrick
  import matplotlib.pyplot
  from yellowbrick.classifier.threshold import *
  from yellowbrick.datasets import load_occupancy, load_spam
  from yellowbrick.utils import is_probabilistic, is_classifier
  from unittest.mock import patch
  from tests.base import VisualTestCase
  from numpy.testing import assert_array_equal
  from sklearn.base import ClassifierMixin
  from sklearn.svm import LinearSVC, NuSVC
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import Pipeline
  from sklearn.datasets import make_classification
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.naive_bayes import BernoulliNB, GaussianNB
  from sklearn.linear_model import Ridge, LogisticRegression
  from sklearn.model_selection import StratifiedShuffleSplit
label_desc: Use image node_id 5 for calling the TestDiscriminationThreshold obj's underlying member method code with example usage: obj.test_quick_method() without return types