class_docstr: DiscriminationThreshold visualizer tests
class_docstr_tok: ["DiscriminationThreshold","visualizer","tests"]
docstr: Correctly generates visualization with alternate arguments
code: def test_binary_discrimination_threshold_alt_args(self):
      """
      Correctly generates visualization with alternate arguments
      """
      X, y = make_classification(
          n_samples=400,
          n_features=20,
          n_informative=10,
          n_redundant=3,
          n_classes=2,
          n_clusters_per_class=4,
          random_state=1231,
          flip_y=0.1,
          weights=[0.35, 0.65],
      )
  
      exclude = ["queue_rate", "fscore"]
      cv = StratifiedShuffleSplit(n_splits=1, test_size=0.2)
      visualizer = DiscriminationThreshold(
          NuSVC(), exclude=exclude, cv=cv, random_state=98239
      )
  
      visualizer.fit(X, y)
      visualizer.finalize()
  
      for metric in exclude:
          assert metric not in visualizer.cv_scores_
          assert "{}_lower".format(metric) not in visualizer.cv_scores_
          assert "{}_upper".format(metric) not in visualizer.cv_scores_
  
      self.assert_images_similar(visualizer)
  
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 7 for calling the TestDiscriminationThreshold obj's underlying member method code with example usage: obj.test_binary_discrimination_threshold_alt_args() without return types