code: def test_default_configuration_regression(self):
      for i in range(5):
          X_train, Y_train, X_test, Y_test = get_dataset(
              dataset="diabetes"
          )
          configuration_space = (
              FastICA.get_hyperparameter_search_space()
          )
          default = configuration_space.get_default_configuration()
          preprocessor = FastICA(
              random_state=1,
              **{hp_name: default[hp_name] for hp_name in default},
          )
          preprocessor.fit(X_train, Y_train)
          X_train_trans = preprocessor.transform(X_train)
          X_test_trans = preprocessor.transform(X_test)
  
          # fit a classifier on top
          classifier = Ridge()
          predictor = classifier.fit(X_train_trans, Y_train)
          predictions = predictor.predict(X_test_trans)
          accuracy = sklearn.metrics.r2_score(Y_test, predictions)
          self.assertAlmostEqual(accuracy, 0.32614416980439365)
  
file_path: auto-sklearn/test/test_pipeline/components/feature_preprocessing/test_fast_ica.py
imports: import sklearn.metrics
  from sklearn.linear_model import Ridge
  from autosklearn.pipeline.components.feature_preprocessing.fast_ica import FastICA
  from autosklearn.pipeline.util import PreprocessingTestCase, _test_preprocessing, get_dataset
  import unittest
label_desc: Use image node_id 2 for calling the FastICAComponentTest obj's underlying member method code with example usage: obj.test_default_configuration_regression() without return types