code: def test_binary_classification(binary_mock_dataset_and_probabilities):
      # Arrange
      text_data, _, proba_test = binary_mock_dataset_and_probabilities
      check = PropertySegmentsPerformance()
  
      # Act
      result = check.run(text_data, probabilities=proba_test)
  
      # Assert
      assert_that(
          result.value["message"],
          equal_to(
              "WeakSegmentsPerformance was unable to train an error model to find"
              " weak segments.Try supplying additional properties."
          ),
      )
  
file_path: deepchecks/tests/nlp/checks/model_evaluation/weak_segment_performance_test.py
imports: import numpy
  import pandas
  import pytest
  from hamcrest import assert_that, calling, close_to, equal_to, has_items, is_in, matches_regexp, raises
  from deepchecks.core.errors import DeepchecksNotSupportedError, NotEnoughSamplesError
  from deepchecks.nlp.checks import MetadataSegmentsPerformance, PropertySegmentsPerformance
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 8 for calling a global function with example usage: test_binary_classification(binary_mock_dataset_and_probabilities) without return types