code: def assertClassifierWorksWithCV(self, classifier):
      # all the nice stuff is tested here - whether the classifier is
      # clonable, etc.
      for X, y in self.get_multilabel_data_for_tests("dense"):
          n_iterations = 3
          cv = model_selection.ShuffleSplit(
              n_splits=n_iterations, test_size=0.5, random_state=0
          )
  
          scores = model_selection.cross_val_score(
              classifier, X, y=y, cv=cv, scoring="accuracy"
          )
  
          self.assertEqual(len(scores), n_iterations)
  
file_path: scikit-multilearn/skmultilearn/tests/classifier_basetest.py
imports: import unittest
  from sklearn import model_selection
  import numpy
  import scipy.sparse
  from .example import EXAMPLE_X, EXAMPLE_y
label_desc: Use image node_id 3 for calling the ClassifierBaseTest obj's underlying member method code with example usage: obj.assertClassifierWorksWithCV(classifier) without return types