code: def test_default_iris_iterative_fit(self):
      if self.__class__ == BaseClassificationComponentTest:
          return
  
      if not hasattr(self.module, "iterative_fit"):
          return
  
      for i in range(2):
          (
              predictions,
              targets,
              classifier,
          ) = _test_classifier_iterative_fit(
              dataset="iris", classifier=self.module
          )
          self.assertAlmostEqual(
              self.res["default_iris_iterative"],
              sklearn.metrics.accuracy_score(targets, predictions),
              places=self.res.get("default_iris_iterative_places", 7),
          )
  
          if self.step_hyperparameter is not None:
              self.assertEqual(
                  getattr(
                      classifier.estimator,
                      self.step_hyperparameter["name"],
                  ),
                  self.res.get(
                      "iris_iterative_n_iter",
                      self.step_hyperparameter["value"],
                  ),
              )
  
imports: from typing import Dict, Optional
  import numpy
  import sklearn.metrics
  from autosklearn.pipeline.constants import SPARSE
  from autosklearn.pipeline.util import _test_classifier, _test_classifier_iterative_fit, _test_classifier_predict_proba
  import unittest
  from test.test_pipeline.ignored_warnings import classifier_warnings, ignore_warnings
label_desc: Use image node_id 3 for calling the BaseClassificationComponentTest obj's underlying member method code with example usage: obj.test_default_iris_iterative_fit() without return types