code: def test_GradientBoostingRegression(self):
      boston = datasets.load_boston()
      df = pdml.ModelFrame(boston)
  
      params = {
          "n_estimators": 500,
          "max_depth": 4,
          "min_samples_split": 0.9,
          "learning_rate": 0.01,
          "loss": "ls",
          "random_state": self.random_state,
      }
      clf1 = ensemble.GradientBoostingRegressor(**params)
      clf2 = df.ensemble.GradientBoostingRegressor(**params)
  
      clf1.fit(boston.data, boston.target)
      df.fit(clf2)
  
      expected = clf1.predict(boston.data)
      predicted = df.predict(clf2)
      self.assertIsInstance(predicted, pdml.ModelSeries)
      self.assert_numpy_array_almost_equal(predicted.values, expected)
  
      self.assertAlmostEqual(
          df.metrics.mean_squared_error(),
          metrics.mean_squared_error(boston.target, expected),
      )
  
file_path: pandas-ml/pandas_ml/skaccessors/test/test_ensemble.py
imports: import pytest
  import sklearn.datasets
  import sklearn.ensemble
  import sklearn.metrics
  import pandas_ml
  import pandas_ml.util.testing
label_desc: Use image node_id 6 for calling the TestEnsemble obj's underlying member method code with example usage: obj.test_GradientBoostingRegression() without return types