class_docstr: Test class for second set of voting learner API tests.
class_docstr_tok: ["Test","class","for","second","set","of","voting","learner","API","tests","."]
code: def test_learning_curve_min_examples_check(self):
      # generates a training split with less than 500 examples
      fs_less_than_500 = FS_DIGITS[:499]
  
      # create a simple voting classifier
      voting_learner = VotingLearner(
          ["LogisticRegression", "SVC", "MultinomialNB"], voting="hard"
      )
  
      # this must throw an error because `examples` has less than 500 items
      with self.assertRaises(ValueError):
          _ = voting_learner.learning_curve(
              examples=fs_less_than_500, metric="accuracy"
          )
  
imports: import re
  import unittest
  from itertools import product
  import numpy
  from numpy.testing import assert_raises_regex
  from scipy.stats import pearsonr
  from sklearn.ensemble import VotingClassifier, VotingRegressor
  from sklearn.metrics import accuracy_score, f1_score, mean_squared_error
  from sklearn.model_selection import ShuffleSplit, learning_curve
  from sklearn.pipeline import Pipeline
  from skll.learner import Learner
  from skll.learner.voting import VotingLearner
  from skll.utils.logging import close_and_remove_logger_handlers, get_skll_logger
  from skll.utils.testing import make_california_housing_data, make_digits_data, other_dir, output_dir
label_desc: Use image node_id 7 for calling the TestVotingLearnersAPITwo obj's underlying member method code with example usage: obj.test_learning_curve_min_examples_check() without return types