code: def test_regression_reduced(diabetes_split_dataset_and_model):
      # Arrange
      _, test, model = diabetes_split_dataset_and_model
      check = SingleDatasetPerformance()
      # Act
      result = check.run(test, model).reduce_output()
      # Assert
      assert_that(result["RMSE"], close_to(57.412, 0.001))
  
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 19 for calling a global function with example usage: test_regression_reduced(diabetes_split_dataset_and_model) without return types