code: def test_can_run_classification_no_proba(
      iris_split_dataset_and_model,
  ):
      ds, _, clf = iris_split_dataset_and_model
      (
          y_pred_train,
          y_pred_test,
          y_proba_train,
          y_proba_test,
      ) = _dummify_model(ds, None, clf)
      y_proba_train = None
      y_proba_test = None
  
      check = SingleDatasetPerformance().add_condition_greater_than(0.9)
      result = check.conditions_decision(
          check.run(
              ds,
              y_pred_train=y_pred_train,
              y_pred_test=y_pred_test,
              y_proba_train=y_proba_train,
              y_proba_test=y_proba_test,
          )
      )
  
      assert_that(
          result,
          has_items(
              equal_condition_result(
                  is_pass=True,
                  details="Passed for all of the metrics.",
                  name="Selected metrics scores are greater than 0.9",
              )
          ),
      )
  
imports: from hamcrest import assert_that, calling, close_to, has_items, raises
  from deepchecks.core.check_result import CheckResult
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.core.errors import DeepchecksValueError, ValidationError
  from deepchecks.tabular.base_checks import TrainTestCheck
  from deepchecks.tabular.checks import SingleDatasetPerformance
  from deepchecks.tabular.checks.model_evaluation.regression_error_distribution import RegressionErrorDistribution
  from deepchecks.tabular.checks.model_evaluation.roc_report import RocReport
  from deepchecks.tabular.checks.model_evaluation.simple_model_comparison import SimpleModelComparison
  from deepchecks.tabular.context import Context
  from deepchecks.tabular.dataset import Dataset
  from deepchecks.tabular.suites.default_suites import full_suite
  from deepchecks.tabular.utils.task_type import TaskType
  from tests.base.utils import equal_condition_result
  from tests.common import get_expected_results_length, validate_suite_result
  from tests.tabular.checks.model_evaluation.simple_model_comparison_test import assert_regression
label_desc: Use image node_id 3 for calling a global function with example usage: test_can_run_classification_no_proba(iris_split_dataset_and_model) without return types