regression.py 文件源码

def get_lipschitz(data):
    """Get the Lipschitz constant for a specific loss function.

    Only square loss implemented.

    Parameters
    ----------
    data : (n, d) float ndarray
        data matrix
    loss : string
        the selected loss function in {'square', 'logit'}
    Returns
    ----------
    L : float
        the Lipschitz constant
    """
    n, p = data.shape

    if p > n:
        tmp = np.dot(data, data.T)
    else:
        tmp = np.dot(data.T, data)
    return la.norm(tmp, 2)