org.opencv.ml

Class CvGBTreesParams

java.lang.Object

org.opencv.ml.CvDTreeParams

org.opencv.ml.CvGBTreesParams

public class CvGBTreesParams
extends CvDTreeParams

GBT training parameters.

The structure contains parameters for each single decision tree in the ensemble, as well as the whole model characteristics. The structure is derived from "CvDTreeParams" but not all of the decision tree parameters are supported: cross-validation, pruning, and class priorities are not used.

See Also:

org.opencv.ml.CvGBTreesParams : public CvDTreeParams

Constructor Summary

Constructors

Constructor and Description
CvGBTreesParams() By default the following constructor is used: CvGBTreesParams(CvGBTrees.SQUARED_LOSS, 200, 0.8f, 0.01f, 3, false)

Method Summary

Methods

Modifier and Type	Method and Description
int	get_loss_function_type()
float	get_shrinkage()
float	get_subsample_portion()
int	get_weak_count()
void	set_loss_function_type(int loss_function_type)
void	set_shrinkage(float shrinkage)
void	set_subsample_portion(float subsample_portion)
void	set_weak_count(int weak_count)

Methods inherited from class org.opencv.ml.CvDTreeParams

get_cv_folds, get_max_categories, get_max_depth, get_min_sample_count, get_regression_accuracy, get_truncate_pruned_tree, get_use_1se_rule, get_use_surrogates, set_cv_folds, set_max_categories, set_max_depth, set_min_sample_count, set_regression_accuracy, set_truncate_pruned_tree, set_use_1se_rule, set_use_surrogates

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

CvGBTreesParams

public CvGBTreesParams()

By default the following constructor is used: CvGBTreesParams(CvGBTrees.SQUARED_LOSS, 200, 0.8f, 0.01f, 3, false)

// C++ code:

: CvDTreeParams(3, 10, 0, false, 10, 0, false, false, 0)

See Also:

org.opencv.ml.CvGBTreesParams.CvGBTreesParams

Method Detail

get_loss_function_type

public int get_loss_function_type()

get_shrinkage

public float get_shrinkage()

get_subsample_portion

public float get_subsample_portion()

get_weak_count

public int get_weak_count()

set_loss_function_type

public void set_loss_function_type(int loss_function_type)

set_shrinkage

public void set_shrinkage(float shrinkage)

set_subsample_portion

public void set_subsample_portion(float subsample_portion)

set_weak_count

public void set_weak_count(int weak_count)