[ VIGRA Homepage | Function Index | Class Index | Namespaces | File List | Main Page ]

details NonlinearLSQOptions Class Reference VIGRA

Pass options to nonlinearLeastSquares(). More...

#include <vigra/regression.hxx>

Public Member Functions

NonlinearLSQOptions & dampingParamters (double lambda, double v)
 Set damping parameters for Levenberg-Marquardt algorithm. More...
 
NonlinearLSQOptions & maxIterations (int iter)
 Set maximum number of iterations. More...
 
 NonlinearLSQOptions ()
 Initialize options with default values.
 
NonlinearLSQOptions & tolerance (double eps)
 Set minimum relative improvement in residual. More...
 

Detailed Description

Pass options to nonlinearLeastSquares().

#include <vigra/regression.hxx> Namespace: vigra

Member Function Documentation

NonlinearLSQOptions& tolerance ( double  eps)

Set minimum relative improvement in residual.

The algorithm stops when the relative improvement in residuals between consecutive iterations is less than this value.

Default: 0 (i.e. choose tolerance automatically, will be 10*epsilon of the numeric type)

NonlinearLSQOptions& maxIterations ( int  iter)

Set maximum number of iterations.

Default: 50

NonlinearLSQOptions& dampingParamters ( double  lambda,
double  v 
)

Set damping parameters for Levenberg-Marquardt algorithm.

lambda determines by how much the diagonal is emphasized, and v is the factor by which lambda will be increased if more damping is needed for convergence (see Wikipedia for more explanations).

Default: lambda = 0.1, v = 1.4


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

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de)
Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

html generated using doxygen and Python
vigra 1.11.1 (Fri May 19 2017)