code: def test_classification_string_labels(iris_labeled_dataset):
      # Arrange
      check = SingleDatasetPerformance()
      replace_dict = {
          iris_labeled_dataset.label_name: {0: "b", 1: "e", 2: "a"}
      }
      iris_labeled_dataset = Dataset(
          iris_labeled_dataset.data.replace(replace_dict),
          label=iris_labeled_dataset.label_name,
      )
  
      iris_adaboost = AdaBoostClassifier(random_state=0)
      iris_adaboost.fit(
          iris_labeled_dataset.data[iris_labeled_dataset.features],
          iris_labeled_dataset.data[iris_labeled_dataset.label_name],
      )
      # Act
      result = check.run(iris_labeled_dataset, iris_adaboost).value
      # Assert
      assert_multiclass_classification_result(result)
  
imports: from typing import List
  from hamcrest import assert_that, calling, close_to, equal_to, has_entries, has_items, has_length, instance_of, none, raises
  from sklearn.ensemble import AdaBoostClassifier, RandomForestClassifier
  from sklearn.model_selection import train_test_split
  from deepchecks.core import ConditionResult
  from deepchecks.core.errors import DeepchecksNotSupportedError, DeepchecksValueError, ModelValidationError
  from deepchecks.tabular.checks import SingleDatasetPerformance
  from deepchecks.tabular.dataset import Dataset
  from deepchecks.tabular.metric_utils.scorers import DEFAULT_MULTICLASS_SCORERS, DEFAULT_REGRESSION_SCORERS
  from tests.base.utils import equal_condition_result
  from tests.common import is_nan
label_desc: Use image node_id 14 for calling a global function with example usage: test_classification_string_labels(iris_labeled_dataset) without return types