def METHOD_NAME():
    ignored = (
        River2SKLBase,
        SKL2RiverBase,
        compose.FuncTransformer,
        compose.Grouper,
        compose.Pipeline,
        compose.Prefixer,
        compose.Renamer,
        compose.Suffixer,
        compose.TargetTransformRegressor,
        facto.FFMClassifier,
        facto.FFMRegressor,
        facto.FMClassifier,
        facto.FMRegressor,
        facto.FwFMClassifier,
        facto.FwFMRegressor,
        facto.HOFMClassifier,
        facto.HOFMRegressor,
        feature_extraction.Agg,
        feature_extraction.TargetAgg,
        feature_selection.PoissonInclusion,
        imblearn.RandomOverSampler,
        imblearn.RandomUnderSampler,
        imblearn.RandomSampler,
        model_selection.SuccessiveHalvingClassifier,
        neighbors.LazySearch,
        neural_net.MLPRegressor,
        preprocessing.PreviousImputer,
        preprocessing.OneHotEncoder,
        preprocessing.StatImputer,
        time_series.base.Forecaster,
    )
    if PYTORCH_INSTALLED:
        ignored = (*ignored, PyTorch2RiverBase)
    def can_be_tested(estimator):
        return not inspect.isabstract(estimator) and not issubclass(estimator, ignored)
    for estimator in filter(can_be_tested, iter_estimators()):
        for params in estimator._unit_test_params():
            yield estimator(**params)