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# `sklearn.utils.estimator_checks`.parametrize_with_checks

sklearn.utils.estimator_checks.parametrize_with_checks(estimators)

  Pytest specific decorator for parametrizing estimator checks.

  The `id` of each check is set to be a pprint version of the estimator and the name of the check with its keyword arguments. This allows to use `pytest -k` to specify which tests to run:

      pytest test_check_estimators.py -k check_estimators_fit_returns_self

  Parameters:
    estimators list of estimators instances

      Estimators to generated checks for.

      Changed in version 0.24: Passing a class was deprecated in version 0.23, and support for classes was removed in 0.24. Pass an instance instead.

      New in version 0.24.

  Returns:
    decorator `pytest.mark.parametrize`

  See also

  `check_estimator`

    Check if estimator adheres to scikit-learn conventions.

  Examples

      >>> from sklearn.utils.estimator_checks import parametrize_with_checks
      >>> from sklearn.linear_model import LogisticRegression
      >>> from sklearn.tree import DecisionTreeRegressor

      >>> @parametrize_with_checks([LogisticRegression(),
      ...                           DecisionTreeRegressor()])
      ... def test_sklearn_compatible_estimator(estimator, check):
      ...     check(estimator)

## Examples using `sklearn.utils.estimator_checks.parametrize_with_checks`

Release Highlights for scikit-learn 0.22

Release Highlights for scikit-learn 0.22