code: def test_default_configuration(self):
      transformation, original = _test_preprocessing(
          SelectClassificationRates
      )
      self.assertEqual(transformation.shape[0], original.shape[0])
      self.assertEqual(transformation.shape[1], 3)
      self.assertFalse((transformation == 0).all())
  
      transformation, original = _test_preprocessing(
          SelectClassificationRates, make_sparse=True
      )
      self.assertTrue(scipy.sparse.issparse(transformation))
      self.assertEqual(transformation.shape[0], original.shape[0])
      self.assertEqual(
          transformation.shape[1], int(original.shape[1] / 2)
      )
  
      # Custom preprocessing test to check if clipping to zero works
      X_train, Y_train, X_test, Y_test = get_dataset(dataset="digits")
      original_X_train = X_train.copy()
      ss = sklearn.preprocessing.StandardScaler()
      X_train = ss.fit_transform(X_train)
      configuration_space = (
          SelectClassificationRates.get_hyperparameter_search_space()
      )
      default = configuration_space.get_default_configuration()
  
      preprocessor = SelectClassificationRates(
          random_state=1,
          **{
              hp_name: default[hp_name]
              for hp_name in default
              if default[hp_name] is not None
          },
      )
  
      transformer = preprocessor.fit(X_train, Y_train)
      transformation, original = (
          transformer.transform(X_train),
          original_X_train,
      )
      self.assertEqual(transformation.shape[0], original.shape[0])
      # I don't know why it's 52 here and not 32 which would be half of the
      # number of features. Seems to be related to a runtime warning raised
      #  by sklearn
      self.assertEqual(transformation.shape[1], 52)
  
file_path: auto-sklearn/test/test_pipeline/components/feature_preprocessing/test_select_rates_classification.py
imports: import numpy
  import scipy.sparse
  import sklearn.preprocessing
  from autosklearn.pipeline.components.feature_preprocessing.select_rates_classification import SelectClassificationRates
  from autosklearn.pipeline.util import _test_preprocessing, get_dataset
  import unittest
label_desc: Use image node_id 1 for calling the SelectClassificationRatesComponentTest obj's underlying member method code with example usage: obj.test_default_configuration() without return types