base_optimizer Class Reference

Base optimizer class. More...

#include <gradopt.h>

Inheritance diagram for base_optimizer:

Public Member Functions
virtual int	SetAccuracy (double max_df=-1, double max_dx=-1, int max_convit=2, double max_grad=-1)
	Set convergence creiteria: max_df – maximal function variance at convergence OR; maximal position variance at convergence, dx is normalized by total variable number OR maximal gradient norm max_grad at convergence.

Detailed Description

Base optimizer class.

Member Function Documentation

SetAccuracy()

virtual int base_optimizer::SetAccuracy ( double  max_df = -1, double  max_dx = -1, int  max_convit = 2, double  max_grad = -1  )

inlinevirtual

Set convergence creiteria:
max_df – maximal function variance at convergence OR;
maximal position variance at convergence, dx is normalized by total variable number OR
maximal gradient norm max_grad at convergence.

Negative parameters mean that the corresponding criteria are not checked. These conditions have to be repeated for at least max_convit consecutive iterations.

Reimplemented in md_grad_optimizer< term_t >.

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The documentation for this class was generated from the following file:

• gradopt.h