cv::ml::ParamGrid Class Reference

The structure represents the logarithmic grid range of statmodel parameters. More...

#include <opencv2/ml.hpp>

Collaboration diagram for cv::ml::ParamGrid:

Public Member Functions
	ParamGrid ()
	Default constructor.
	ParamGrid (double _minVal, double _maxVal, double _logStep)
	Constructor with parameters.

Static Public Member Functions
static Ptr< ParamGrid >	create (double minVal=0., double maxVal=0., double logstep=1.)
	Creates a ParamGrid Ptr that can be given to the SVM::trainAuto method.

Public Attributes
double	logStep
	Logarithmic step for iterating the statmodel parameter.
double	maxVal
	Maximum value of the statmodel parameter. Default value is 0.
double	minVal
	Minimum value of the statmodel parameter. Default value is 0.

Detailed Description

The structure represents the logarithmic grid range of statmodel parameters.

It is used for optimizing statmodel accuracy by varying model parameters, the accuracy estimate being computed by cross-validation.

Constructor & Destructor Documentation

ParamGrid() [1/2]

cv::ml::ParamGrid::ParamGrid

(

)

Default constructor.

ParamGrid() [2/2]

cv::ml::ParamGrid::ParamGrid	(	double	_minVal,
		double	_maxVal,
		double	_logStep )

Constructor with parameters.

Member Function Documentation

create()

static Ptr< ParamGrid > cv::ml::ParamGrid::create ( double minVal = 0., double maxVal = 0., double logstep = 1. )

static

Python:
	cv.ml.ParamGrid.create(	[, minVal[, maxVal[, logstep]]]	) ->	retval
	cv.ml.ParamGrid_create(	[, minVal[, maxVal[, logstep]]]	) ->	retval

Creates a ParamGrid Ptr that can be given to the SVM::trainAuto method.

Parameters

minVal	minimum value of the parameter grid
maxVal	maximum value of the parameter grid
logstep	Logarithmic step for iterating the statmodel parameter

Member Data Documentation

logStep

double cv::ml::ParamGrid::logStep

Logarithmic step for iterating the statmodel parameter.

The grid determines the following iteration sequence of the statmodel parameter values:

\[(minVal, minVal*step, minVal*{step}^2, \dots, minVal*{logStep}^n),\]

where \(n\) is the maximal index satisfying

\[\texttt{minVal} * \texttt{logStep} ^n < \texttt{maxVal}\]

The grid is logarithmic, so logStep must always be greater than 1. Default value is 1.

maxVal

double cv::ml::ParamGrid::maxVal

Maximum value of the statmodel parameter. Default value is 0.

minVal

double cv::ml::ParamGrid::minVal

Minimum value of the statmodel parameter. Default value is 0.

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

• opencv2/ml.hpp