public class LBFGS
:: DeveloperApi ::
Class used to solve an optimization problem using Limited-memory BFGS.
Wikipedia on Limited-memory BFGS
param: gradient Gradient function to be used.
param: updater Updater to be used to update weights after every iteration.
Set the number of corrections used in the LBFGS update. Default 10.
Values of numCorrections less than 3 are not recommended; large values
of numCorrections will result in excessive computing time.
numCorrections must be positive, and values from 4 to 9 are generally recommended.
Set the convergence tolerance of iterations for L-BFGS. Default 1E-6.
Smaller value will lead to higher accuracy with the cost of more iterations.
This value must be nonnegative. Lower convergence values are less tolerant
and therefore generally cause more iterations to be run.
Set the updater function to actually perform a gradient step in a given direction.
The updater is responsible to perform the update from the regularization term as well,
and therefore determines what kind or regularization is used, if any.