def test_get_hyperparameter_search_space(self):
cs = SimpleClassificationPipeline().get_hyperparameter_search_space()
self.assertIsInstance(cs, ConfigurationSpace)
conditions = cs.get_conditions()
forbiddens = cs.get_forbiddens()
self.assertEqual(
len(
cs.get_hyperparameter(
'data_preprocessing:numerical_transformer:rescaling:__choice__'
).choices), 7)
self.assertEqual(
len(cs.get_hyperparameter('classifier:__choice__').choices), 16)
self.assertEqual(
len(
cs.get_hyperparameter(
'feature_preprocessor:__choice__').choices), 13)
hyperparameters = cs.get_hyperparameters()
self.assertEqual(167, len(hyperparameters))
# for hp in sorted([str(h) for h in hyperparameters]):
# print hp
# The four components which are always active are classifier,
# feature preprocessor, balancing and data preprocessing pipeline.
self.assertEqual(len(hyperparameters) - 7, len(conditions))
self.assertEqual(len(forbiddens), 53)
def test_get_hyperparameter_search_space(self):
cs = SimpleClassificationPipeline().get_hyperparameter_search_space()
self.assertIsInstance(cs, ConfigurationSpace)
conditions = cs.get_conditions()
self.assertEqual(len(cs.get_hyperparameter(
'rescaling:__choice__').choices), 6)
self.assertEqual(len(cs.get_hyperparameter(
'classifier:__choice__').choices), 16)
self.assertEqual(len(cs.get_hyperparameter(
'preprocessor:__choice__').choices), 13)
hyperparameters = cs.get_hyperparameters()
self.assertEqual(172, len(hyperparameters))
#for hp in sorted([str(h) for h in hyperparameters]):
# print hp
# The four parameters which are always active are classifier,
# preprocessor, imputation strategy and scaling strategy
self.assertEqual(len(hyperparameters) - 6, len(conditions))
def test_get_hyperparameter_search_space(self):
cs = SimpleClassificationPipeline().get_hyperparameter_search_space()
self.assertIsInstance(cs, ConfigurationSpace)
conditions = cs.get_conditions()
self.assertEqual(
len(cs.get_hyperparameter('rescaling:__choice__').choices), 6)
self.assertEqual(
len(cs.get_hyperparameter('classifier:__choice__').choices), 15)
self.assertEqual(
len(cs.get_hyperparameter('preprocessor:__choice__').choices), 13)
hyperparameters = cs.get_hyperparameters()
self.assertEqual(156, len(hyperparameters))
#for hp in sorted([str(h) for h in hyperparameters]):
# print hp
# The four parameters which are always active are classifier,
# preprocessor, imputation strategy and scaling strategy
self.assertEqual(len(hyperparameters) - 6, len(conditions))
