code: def test_confusion_matrix_report_display(
      iris_split_dataset_and_model,
  ):
      # Arrange
      _, test, clf = iris_split_dataset_and_model
  
      # Act
      check = ConfusionMatrixReport()
  
      result = check.run(test, clf)
  
      # Assert
      assert_that(
          result.display[0],
          equal_to(
              "The overall accuracy of your model is: 91.67%.<br>Best accuracy achieved on samples with <b>"
              "0</b> label (100.0%).<br>Worst accuracy achieved on samples with <b>2</b> label (75.0%)."
          ),
      )
      # # First is the text description and second is the heatmap
      assert_that(len(result.display), equal_to(2))
      assert_that(len(result.display[1].data), equal_to(1))
      assert_that(result.display[1].data[0].type, equal_to("heatmap"))
  
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 10 for calling a global function with example usage: test_confusion_matrix_report_display(iris_split_dataset_and_model) without return types