def test_default_configuration_iterative_fit(self):
regressor = SimpleRegressionPipeline(
include={'regressor': ['random_forest'],
'preprocessor': ['no_preprocessing']})
X_train, Y_train, X_test, Y_test = get_dataset(dataset='boston')
XT = regressor.pre_transform(X_train, Y_train)
for i in range(1, 11):
regressor.iterative_fit(X_train, Y_train)
self.assertEqual(regressor.steps[-1][-1].choice.estimator.n_estimators,
i)
