OpenCV Random Forest parameters. More...

#include <TrainNodeCvRF.h>

Public Member Functions
	TrainNodeCvRFParams ()

	TrainNodeCvRFParams (int _max_depth, int _min_sample_count, float _regression_accuracy, bool _use_surrogates, int _max_categories, bool _calc_var_importance, int _nactive_vars, int _maxCount, double _epsilon, int _term_criteria_type, size_t _maxSamples)

Public Attributes
int	max_depth
	Max depth. More...

int	min_sample_count
	Min sample count (1% of all data) More...

float	regression_accuracy
	Regression accuracy (0 means N/A here) More...

bool	use_surrogates
	Compute surrogate split, no missing data. More...

int	max_categories
	Max number of categories (use sub-optimal algorithm for larger numbers) More...

bool	calc_var_importance
	Calculate variable importance (must be true in order to use CTrainNodeCvRF::getFeatureImportance function) More...

int	nactive_vars
	Number of variables randomly selected at node and used to find the best split(s). (0 means the \( \sqrt{nFeatures} \)) More...

int	maxCount
	Max number of trees in the forest (time / accuracy) More...

double	epsilon
	Forest accuracy. More...

int	term_criteria_type
	Termination cirteria type (according the the two previous parameters) More...

size_t	maxSamples
	Maximum number of samples to be used in training. 0 means using all the samples. More...

Detailed Description

OpenCV Random Forest parameters.

Definition at line 13 of file TrainNodeCvRF.h.

Constructor & Destructor Documentation

◆ TrainNodeCvRFParams() [1/2]

DirectGraphicalModels::TrainNodeCvRFParams::TrainNodeCvRFParams ( )

inline

Definition at line 26 of file TrainNodeCvRF.h.

◆ TrainNodeCvRFParams() [2/2]

DirectGraphicalModels::TrainNodeCvRFParams::TrainNodeCvRFParams	(	int	_max_depth,
		int	_min_sample_count,
		float	_regression_accuracy,
		bool	_use_surrogates,
		int	_max_categories,
		bool	_calc_var_importance,
		int	_nactive_vars,
		int	_maxCount,
		double	_epsilon,
		int	_term_criteria_type,
		size_t	_maxSamples
	)

inline

Definition at line 27 of file TrainNodeCvRF.h.

Member Data Documentation

◆ calc_var_importance

bool DirectGraphicalModels::TrainNodeCvRFParams::calc_var_importance

Calculate variable importance (must be true in order to use CTrainNodeCvRF::getFeatureImportance function)

Definition at line 19 of file TrainNodeCvRF.h.

◆ epsilon

double DirectGraphicalModels::TrainNodeCvRFParams::epsilon

Forest accuracy.

Definition at line 22 of file TrainNodeCvRF.h.

◆ max_categories

int DirectGraphicalModels::TrainNodeCvRFParams::max_categories

Max number of categories (use sub-optimal algorithm for larger numbers)

Definition at line 18 of file TrainNodeCvRF.h.

◆ max_depth

int DirectGraphicalModels::TrainNodeCvRFParams::max_depth

Max depth.

Definition at line 14 of file TrainNodeCvRF.h.

◆ maxCount

int DirectGraphicalModels::TrainNodeCvRFParams::maxCount

Max number of trees in the forest (time / accuracy)

Definition at line 21 of file TrainNodeCvRF.h.

◆ maxSamples

size_t DirectGraphicalModels::TrainNodeCvRFParams::maxSamples

Maximum number of samples to be used in training. 0 means using all the samples.

Definition at line 24 of file TrainNodeCvRF.h.

◆ min_sample_count

int DirectGraphicalModels::TrainNodeCvRFParams::min_sample_count

Min sample count (1% of all data)

Definition at line 15 of file TrainNodeCvRF.h.

◆ nactive_vars

int DirectGraphicalModels::TrainNodeCvRFParams::nactive_vars

Number of variables randomly selected at node and used to find the best split(s). (0 means the \( \sqrt{nFeatures} \))

Definition at line 20 of file TrainNodeCvRF.h.

◆ regression_accuracy

float DirectGraphicalModels::TrainNodeCvRFParams::regression_accuracy

Regression accuracy (0 means N/A here)

Definition at line 16 of file TrainNodeCvRF.h.

◆ term_criteria_type

int DirectGraphicalModels::TrainNodeCvRFParams::term_criteria_type

Termination cirteria type (according the the two previous parameters)

Definition at line 23 of file TrainNodeCvRF.h.

◆ use_surrogates

bool DirectGraphicalModels::TrainNodeCvRFParams::use_surrogates

Compute surrogate split, no missing data.

Definition at line 17 of file TrainNodeCvRF.h.

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

D:/Projects/DGM/modules/DGM/TrainNodeCvRF.h

Public Member Functions

Public Attributes