code: def test_balance_classes_without_cramers_v(drifted_data_and_model):
      # Arrange
      train, test, model = drifted_data_and_model
      train = remove_label(train)
      test = remove_label(test)
      check = PredictionDrift(
          categorical_drift_method="PSI",
          drift_mode="prediction",
          balance_classes=True,
      )
  
      assert_that(
          calling(check.run).with_args(train, test, model),
          raises(
              DeepchecksValueError,
              "balance_classes is only supported for Cramer's V. please set balance_classes=False "
              "or use 'cramers_v' as categorical_drift_method",
          ),
      )
  
imports: import pandas
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_length, raises
  from deepchecks.core.errors import DeepchecksValueError, NotEnoughSamplesError
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.checks import PredictionDrift
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 11 for calling a global function with example usage: test_balance_classes_without_cramers_v(drifted_data_and_model) without return types