sklearn 中sag 、 lbfgs指的是什么？

penalty : str, 'l1' or 'l2', default: 'l2'
    Used to specify the norm used in the penalization. The 'newton-cg',
    'sag' and 'lbfgs' solvers support only l2 penalties.

    .. versionadded:: 0.19
       l1 penalty with SAGA solver (allowing 'multinomial' + L1)

sklearn 中sag 、 lbfgs指的是什么？

Stochastic Gradient Descent (SGD)

solver : {‘auto’, ‘svd’, ‘cholesky’, ‘lsqr’, ‘sparse_cg’, ‘sag’,‘saga’}
Solver to use in the computational routines:

‘auto’ chooses the solver automatically based on the type of data.
‘svd’ uses a Singular Value Decomposition of X to compute the Ridge coefficients. More stable for singular matrices than ‘cholesky’.
‘cholesky’ uses the standard scipy.linalg.solve function to obtain a closed-form solution. ‘sparse_cg’ uses the conjugate gradient solver as found in scipy.sparse.linalg.cg. As an iterative a