template<typename Scalar = double>
class LBFGSpp::LBFGSParam< Scalar >
Parameters to control the L-BFGS algorithm.
Definition at line 68 of file Param.h.
template<typename Scalar = double>
Absolute tolerance for convergence test. This parameter determines the absolute accuracy \(\epsilon_{abs}\) with which the solution is to be found. A minimization terminates when \(||g|| < \max\{\epsilon_{abs}, \epsilon_{rel}||x||\}\), where \(||\cdot||\) denotes the Euclidean (L2) norm. The default value is 1e-5.
Definition at line 88 of file Param.h.
template<typename Scalar = double>
Relative tolerance for convergence test. This parameter determines the relative accuracy \(\epsilon_{rel}\) with which the solution is to be found. A minimization terminates when \(||g|| < \max\{\epsilon_{abs}, \epsilon_{rel}||x||\}\), where \(||\cdot||\) denotes the Euclidean (L2) norm. The default value is 1e-5.
Definition at line 97 of file Param.h.
template<typename Scalar = double>
Distance for delta-based convergence test. This parameter determines the distance \(d\) to compute the rate of decrease of the objective function, \(f_{k-d}(x)-f_k(x)\), where \(k\) is the current iteration step. If the value of this parameter is zero, the delta-based convergence test will not be performed. The default value is 0.
Definition at line 106 of file Param.h.
template<typename Scalar = double>
Delta for convergence test. The algorithm stops when the following condition is met, \(|f_{k-d}(x)-f_k(x)|<\delta\cdot\max(1, |f_k(x)|, |f_{k-d}(x)|)\), where \(f_k(x)\) is the current function value, and \(f_{k-d}(x)\) is the function value \(d\) iterations ago (specified by the past parameter). The default value is 0.
Definition at line 115 of file Param.h.
1.9.6