def test_regression_iterate_seed(self):
elastic_net = linear_model.ElasticNet(random_state=123)
expected_result = bootstrap.regression_iterate(
elastic_net, self.data, self.target, seed=1)
result = bootstrap.regression_iterate(
elastic_net, self.data, self.target, seed=1)
self.assertIsInstance(result, dict)
self.assertEqual(result, expected_result)
def test_regression_iterate_randomize_target(self):
"""Ensures the target randomization delivers different results."""
kw = {'regressor': linear_model.Ridge(),
'data': self.data,
'target': self.target}
bootstrapped_results = bootstrap.regression_iterate(
randomize_target=False, **kw)
randomized_results = bootstrap.regression_iterate(
randomize_target=True, **kw)
# Checks randomize and bootstrap results have same keys.
self.assertEqual(randomized_results.keys(), bootstrapped_results.keys())
# But they have different data.
self.assertNotEqual(
randomized_results.values(), bootstrapped_results.values())
def test_regression_not_numeric_index(self):
"""Makes sure that regression_iterate handles non numeric indexing."""
elastic_net = linear_model.ElasticNet(random_state=123)
data = self.data.copy()
target = self.target.copy()
# Convert index to string for `data` and `target`
data.index = [f'data_{index}' for index in data.index]
target.index = [f'test_{index}' for index in target.index]
expected_result = bootstrap.regression_iterate(
elastic_net, self.data, self.target, seed=1)
result = bootstrap.regression_iterate(
elastic_net, data, target, seed=1)
self.assertIsInstance(result, dict)
self.assertEqual(result, expected_result)
def test_regression_iterate_no_intercept(self):
elastic_net = linear_model.ElasticNet(fit_intercept=False)
expected_keys = set(self.data.columns)
result = bootstrap.regression_iterate(
elastic_net, self.data, self.target, seed=1)
self.assertIsInstance(result, dict)
# Assert all the keys are the DataFrame columns.
self.assertEqual(expected_keys, set(result))
def test_regression_iterate(self):
elastic_net = linear_model.ElasticNet()
expected_keys = set(list(self.data.columns) + ['Intercept'])
result = bootstrap.regression_iterate(
elastic_net, self.data, self.target, seed=1)
self.assertIsInstance(result, dict)
# Assert all the keys are the DataFrame columns plus the intercept.
self.assertEqual(expected_keys, set(result))