Classe « BFGS »

Informations générales

Héritage

builtins.object
    HessianUpdateStrategy
        FullHessianUpdateStrategy
            BFGS

Définition

class BFGS(FullHessianUpdateStrategy):

help(BFGS)

Broyden-Fletcher-Goldfarb-Shanno (BFGS) Hessian update strategy.

Parameters
----------
exception_strategy : {'skip_update', 'damp_update'}, optional
    Define how to proceed when the curvature condition is violated.
    Set it to 'skip_update' to just skip the update. Or, alternatively,
    set it to 'damp_update' to interpolate between the actual BFGS
    result and the unmodified matrix. Both exceptions strategies
    are explained  in [1]_, p.536-537.
min_curvature : float
    This number, scaled by a normalization factor, defines the
    minimum curvature ``dot(delta_grad, delta_x)`` allowed to go
    unaffected by the exception strategy. By default is equal to
    1e-8 when ``exception_strategy = 'skip_update'`` and equal
    to 0.2 when ``exception_strategy = 'damp_update'``.
init_scale : {float, np.array, 'auto'}
    This parameter can be used to initialize the Hessian or its
    inverse. When a float is given, the relevant array is initialized
    to ``np.eye(n) * init_scale``, where ``n`` is the problem dimension.
    Alternatively, if a precisely ``(n, n)`` shaped, symmetric array is given,
    this array will be used. Otherwise an error is generated.
    Set it to 'auto' in order to use an automatic heuristic for choosing
    the initial scale. The heuristic is described in [1]_, p.143.
    The default is 'auto'.

Notes
-----
The update is based on the description in [1]_, p.140.

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