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
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 |
clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
CvRTParams
public CvRTParams()
CvRTParams
protected CvRTParams(long addr)
finalize
protected void finalize()
throws java.lang.Throwable
- Overrides:
finalize
in class CvDTreeParams
- Throws:
java.lang.Throwable
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)