org.opencv.ml
Class CvRTParams

java.lang.Object
  org.opencv.ml.CvDTreeParams
      org.opencv.ml.CvRTParams

public class CvRTParams
extends CvDTreeParams

Training parameters of random trees.

The set of training parameters for the forest is a superset of the training parameters for a single tree. However, random trees do not need all the functionality/features of decision trees. Most noticeably, the trees are not pruned, so the cross-validation parameters are not used.

See Also:

org.opencv.ml.CvRTParams : public CvDTreeParams

Constructor Summary

CvRTParams()

Method Summary

boolean	get_calc_var_importance()
int	get_nactive_vars()
TermCriteria	get_term_crit()
void	set_calc_var_importance(boolean calc_var_importance)
void	set_nactive_vars(int nactive_vars)
void	set_term_crit(TermCriteria term_crit)

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

CvRTParams

public CvRTParams()

Method Detail

get_calc_var_importance

public boolean get_calc_var_importance()

get_nactive_vars

public int get_nactive_vars()

get_term_crit

public TermCriteria get_term_crit()

set_calc_var_importance

public void set_calc_var_importance(boolean calc_var_importance)

set_nactive_vars

public void set_nactive_vars(int nactive_vars)

set_term_crit

public void set_term_crit(TermCriteria term_crit)