Module « scipy.optimize »

Classe « HessianUpdateStrategy »

Informations générales

Héritage

builtins.object
    HessianUpdateStrategy

Définition

class HessianUpdateStrategy(builtins.object):

Description _{[extrait de HessianUpdateStrategy.__doc__]}

Interface for implementing Hessian update strategies.

    Many optimization methods make use of Hessian (or inverse Hessian)
    approximations, such as the quasi-Newton methods BFGS, SR1, L-BFGS.
    Some of these  approximations, however, do not actually need to store
    the entire matrix or can compute the internal matrix product with a
    given vector in a very efficiently manner. This class serves as an
    abstract interface between the optimization algorithm and the
    quasi-Newton update strategies, giving freedom of implementation
    to store and update the internal matrix as efficiently as possible.
    Different choices of initialization and update procedure will result
    in different quasi-Newton strategies.

    Four methods should be implemented in derived classes: ``initialize``,
    ``update``, ``dot`` and ``get_matrix``.

    Notes
    -----
    Any instance of a class that implements this interface,
    can be accepted by the method ``minimize`` and used by
    the compatible solvers to approximate the Hessian (or
    inverse Hessian) used by the optimization algorithms.
    

Liste des opérateurs

Opérateurs hérités de la classe object

__eq__, __ge__, __gt__, __le__, __lt__, __ne__

Méthodes héritées de la classe object

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