def METHOD_NAME(
        self,
        accuracy=None,
        time_tolerance=None,
        interpretability=None,
        **kwargs
):
    # fill up parameters we care about
    self.params = dict(
        random_state=kwargs.get("random_state", 1234),
        n_estimators=min(kwargs.get("n_estimators", 100), 2000),
        criterion="mse",
        max_depth=10,
        min_samples_leaf=10,
        n_jobs=self.params_base.get("n_jobs", max(1, physical_cores_count)),
    )