Module « scipy.optimize »

Classe « SR1 »

Informations générales

Héritage

builtins.object
    HessianUpdateStrategy
        FullHessianUpdateStrategy
            SR1

Définition

class SR1(FullHessianUpdateStrategy):

Description _{[extrait de SR1.__doc__]}

Symmetric-rank-1 Hessian update strategy.

    Parameters
    ----------
    min_denominator : float
        This number, scaled by a normalization factor,
        defines the minimum denominator magnitude allowed
        in the update. When the condition is violated we skip
        the update. By default uses ``1e-8``.
    init_scale : {float, 'auto'}, optional
        Matrix scale at first iteration. At the first
        iteration the Hessian matrix or its inverse will be initialized
        with ``init_scale*np.eye(n)``, where ``n`` is the problem dimension.
        Set it to 'auto' in order to use an automatic heuristic for choosing
        the initial scale. The heuristic is described in [1]_, p.143.
        By default uses 'auto'.

    Notes
    -----
    The update is based on the description in [1]_, p.144-146.

    References
    ----------
    .. [1] Nocedal, Jorge, and Stephen J. Wright. "Numerical optimization"
           Second Edition (2006).
    

Constructeur(s)

Signature du constructeur	Description
__init__(self, min_denominator=1e-08, init_scale='auto')

Liste des opérateurs

Opérateurs hérités de la classe object

__eq__, __ge__, __gt__, __le__, __lt__, __ne__

Méthodes héritées de la classe FullHessianUpdateStrategy

__init_subclass__, __subclasshook__, dot, get_matrix, initialize, update

Méthodes héritées de la classe object

__delattr__, __dir__, __format__, __getattribute__, __hash__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__