code: def test_condition_misclassified_samples_lower_than_passes(
      iris_split_dataset_and_model,
  ):
      # Arrange
      _, test, clf = iris_split_dataset_and_model
  
      threshold = 0.1
  
      # Act
      check = ConfusionMatrixReport().add_condition_misclassified_samples_lower_than_condition(
          misclassified_samples_threshold=threshold
      )
  
      result = check.run(test, clf)
  
      # Assert
      assert_that(
          result.conditions_results[0],
          equal_condition_result(
              is_pass=True,
              name=f"Misclassified cell size lower than {format_percent(threshold)} of the total samples",
              details="All misclassified confusion matrix cells contain less than "
              f"{format_percent(threshold)} of the data.",
          ),
      )
  
file_path: deepchecks/tests/tabular/checks/model_evaluation/confusion_matrix_report_test.py
imports: import numpy
  from hamcrest import assert_that, calling, equal_to, greater_than, has_length, raises
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.core.errors import DeepchecksNotSupportedError, DeepchecksValueError, ModelValidationError
  from deepchecks.tabular.checks.model_evaluation import ConfusionMatrixReport
  from deepchecks.utils.strings import format_number, format_percent
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 8 for calling a global function with example usage: test_condition_misclassified_samples_lower_than_passes(iris_split_dataset_and_model) without return types