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)