def _get_SHA_params(SHA):
    """
    Parameters
    ----------
    SHA : SuccessiveHalvingSearchCV

    Returns
    -------
    params : dict
        Dictionary to re-create a SuccessiveHalvingSearchCV without the
        estimator or parameters

    Example
    -------
    >>> from sklearn.linear_model import SGDClassifier
    >>> model = SGDClassifier()
    >>> params = {"alpha": np.logspace(-1, 1)}
    >>> SHA = SuccessiveHalvingSearchCV(model, params, tol=0.1,
    ...                                 patience=True, random_state=42)
    >>> _get_SHA_params(SHA)
    {'aggressiveness': 3,
     'max_iter': 100,
     'n_initial_iter': 9,
     'n_initial_parameters': 10,
     'patience': True,
     'random_state': 42,
     'scoring': None,
     'test_size': None,
     'tol': 0.1}

    """
    return {
        k: v
        for k, v in SHA.get_params().items()
        if "estimator_" not in k and k != "parameters" and k != "estimator"
    }