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LeastAngleRegressionOptions Class Reference
[Optimization and Regression]

Pass options to leastAngleRegression(). More...

#include <vigra/regression.hxx>

List of all members.

Public Member Functions

LeastAngleRegressionOptionslars ()
LeastAngleRegressionOptionslasso ()
 LeastAngleRegressionOptions ()
LeastAngleRegressionOptionsleastSquaresSolutions (bool select=true)
LeastAngleRegressionOptionsmaxSolutionCount (unsigned int n)
LeastAngleRegressionOptionsnnlasso ()
LeastAngleRegressionOptionssetMode (std::string mode)

Detailed Description

Pass options to leastAngleRegression().

#include <vigra/regression.hxx> Namespaces: vigra and vigra::linalg


Constructor & Destructor Documentation

Initialize all options with default values.


Member Function Documentation

LeastAngleRegressionOptions& maxSolutionCount ( unsigned int  n  ) 

Maximum number of solutions to be computed.

If n is 0 (the default), the number of solutions is determined by the length of the solution array. Otherwise, the minimum of maxSolutionCount() and that length is taken.
Default: 0 (use length of solution array)

LeastAngleRegressionOptions& setMode ( std::string  mode  ) 

Set the mode of the algorithm.

Mode must be one of "lars", "lasso", "nnlasso". The function just calls the member function of the corresponding name to set the mode.

Default: "lasso"

Use the plain LARS algorithm.

Default: inactive

Use the LASSO modification of the LARS algorithm.

This allows features to be removed from the active set under certain conditions.
Default: active

LeastAngleRegressionOptions& nnlasso (  ) 

Use the non-negative LASSO modification of the LARS algorithm.

This enforces all non-zero entries in the solution to be positive.
Default: inactive

LeastAngleRegressionOptions& leastSquaresSolutions ( bool  select = true  ) 

Compute least squares solutions.

Use least angle regression to determine active sets, but return least squares solutions for the features in each active set, instead of constrained solutions.
Default: true


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 1.8.0 (20 Sep 2011)