def check_estimator(Estimator, run_sampler_tests=True):
"""Check if estimator adheres to scikit-learn conventions and
imbalanced-learn
This estimator will run an extensive test-suite for input validation,
shapes, etc.
Additional tests samplers if the Estimator inherits from the corresponding
mixin from imblearn.base
Parameters
----------
Estimator : class
Class to check. Estimator is a class object (not an instance)
run_sampler_tests=True : bool, default=True
Will run or not the samplers tests.
"""
name = Estimator.__name__
# monkey patch check_dtype_object for the sampler allowing strings
import sklearn.utils.estimator_checks
sklearn.utils.estimator_checks.check_dtype_object = \
monkey_patch_check_dtype_object
# scikit-learn common tests
sklearn_check_estimator(Estimator)
check_parameters_default_constructible(name, Estimator)
if run_sampler_tests:
for check in _yield_all_checks(name, Estimator):
check(name, Estimator)
def check_estimator(Estimator, run_sampler_tests=True):
"""Check if estimator adheres to scikit-learn conventions and
imbalanced-learn
This estimator will run an extensive test-suite for input validation,
shapes, etc.
Additional tests samplers if the Estimator inherits from the corresponding
mixin from imblearn.base
Parameters
----------
Estimator : class
Class to check. Estimator is a class object (not an instance)
run_sampler_tests=True : bool, default=True
Will run or not the samplers tests.
"""
name = Estimator.__name__
# monkey patch check_dtype_object for the sampler allowing strings
import sklearn.utils.estimator_checks
sklearn.utils.estimator_checks.check_dtype_object = \
monkey_patch_check_dtype_object
# scikit-learn common tests
sklearn_check_estimator(Estimator)
check_parameters_default_constructible(name, Estimator)
if run_sampler_tests:
for check in _yield_all_checks(name, Estimator):
check(name, Estimator)
def check_estimator(Estimator):
"""Check if estimator adheres to scikit-learn conventions and
imbalanced-learn
This estimator will run an extensive test-suite for input validation,
shapes, etc.
Additional tests samplers if the Estimator inherits from the corresponding
mixin from imblearn.base
Parameters
----------
Estimator : class
Class to check. Estimator is a class object (not an instance).
"""
name = Estimator.__name__
# test scikit-learn compatibility
sklearn_check_estimator(Estimator)
check_parameters_default_constructible(name, Estimator)
for check in _yield_all_checks(name, Estimator):
check(name, Estimator)
def check_estimator(Estimator):
"""Check if estimator adheres to scikit-learn conventions and
imbalanced-learn
This estimator will run an extensive test-suite for input validation,
shapes, etc.
Additional tests samplers if the Estimator inherits from the corresponding
mixin from imblearn.base
Parameters
----------
Estimator : class
Class to check. Estimator is a class object (not an instance).
"""
name = Estimator.__name__
# test scikit-learn compatibility
sklearn_check_estimator(Estimator)
check_parameters_default_constructible(name, Estimator)
for check in _yield_all_checks(name, Estimator):
check(name, Estimator)
