CV_PROP_RW float regression_accuracy;
const float* priors;
- CvDTreeParams() : max_categories(10), max_depth(INT_MAX), min_sample_count(10),
- cv_folds(10), use_surrogates(true), use_1se_rule(true),
- truncate_pruned_tree(true), regression_accuracy(0.01f), priors(0)
- {}
-
- CvDTreeParams( int _max_depth, int _min_sample_count,
- float _regression_accuracy, bool _use_surrogates,
- int _max_categories, int _cv_folds,
- bool _use_1se_rule, bool _truncate_pruned_tree,
- const float* _priors ) :
- max_categories(_max_categories), max_depth(_max_depth),
- min_sample_count(_min_sample_count), cv_folds (_cv_folds),
- use_surrogates(_use_surrogates), use_1se_rule(_use_1se_rule),
- truncate_pruned_tree(_truncate_pruned_tree),
- regression_accuracy(_regression_accuracy),
- priors(_priors)
- {}
+ CvDTreeParams();
+ CvDTreeParams( int max_depth, int min_sample_count,
+ float regression_accuracy, bool use_surrogates,
+ int max_categories, int cv_folds,
+ bool use_1se_rule, bool truncate_pruned_tree,
+ const float* priors );
};
CV_PROP_RW int nactive_vars;
CV_PROP_RW CvTermCriteria term_crit;
- CvRTParams() : CvDTreeParams( 5, 10, 0, false, 10, 0, false, false, 0 ),
- calc_var_importance(false), nactive_vars(0)
- {
- term_crit = cvTermCriteria( CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 50, 0.1 );
- }
-
- CvRTParams( int _max_depth, int _min_sample_count,
- float _regression_accuracy, bool _use_surrogates,
- int _max_categories, const float* _priors, bool _calc_var_importance,
- int _nactive_vars, int max_num_of_trees_in_the_forest,
- float forest_accuracy, int termcrit_type ) :
- CvDTreeParams( _max_depth, _min_sample_count, _regression_accuracy,
- _use_surrogates, _max_categories, 0,
- false, false, _priors ),
- calc_var_importance(_calc_var_importance),
- nactive_vars(_nactive_vars)
- {
- term_crit = cvTermCriteria(termcrit_type,
- max_num_of_trees_in_the_forest, forest_accuracy);
- }
+ CvRTParams();
+ CvRTParams( int max_depth, int min_sample_count,
+ float regression_accuracy, bool use_surrogates,
+ int max_categories, const float* priors, bool calc_var_importance,
+ int nactive_vars, int max_num_of_trees_in_the_forest,
+ float forest_accuracy, int termcrit_type );
};
//////////////////////////////////////////////////////////////////////////////////////////
// Random trees //
//////////////////////////////////////////////////////////////////////////////////////////
+CvRTParams::CvRTParams() : CvDTreeParams( 5, 10, 0, false, 10, 0, false, false, 0 ),
+ calc_var_importance(false), nactive_vars(0)
+{
+ term_crit = cvTermCriteria( CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 50, 0.1 );
+}
+
+CvRTParams::CvRTParams( int _max_depth, int _min_sample_count,
+ float _regression_accuracy, bool _use_surrogates,
+ int _max_categories, const float* _priors, bool _calc_var_importance,
+ int _nactive_vars, int max_num_of_trees_in_the_forest,
+ float forest_accuracy, int termcrit_type ) :
+ CvDTreeParams( _max_depth, _min_sample_count, _regression_accuracy,
+ _use_surrogates, _max_categories, 0,
+ false, false, _priors ),
+ calc_var_importance(_calc_var_importance),
+ nactive_vars(_nactive_vars)
+{
+ term_crit = cvTermCriteria(termcrit_type,
+ max_num_of_trees_in_the_forest, forest_accuracy);
+}
CvRTrees::CvRTrees()
{
}
/////////////////////// Decision Tree /////////////////////////
+CvDTreeParams::CvDTreeParams() : max_categories(10), max_depth(INT_MAX), min_sample_count(10),
+ cv_folds(10), use_surrogates(true), use_1se_rule(true),
+ truncate_pruned_tree(true), regression_accuracy(0.01f), priors(0)
+{}
+
+CvDTreeParams::CvDTreeParams( int _max_depth, int _min_sample_count,
+ float _regression_accuracy, bool _use_surrogates,
+ int _max_categories, int _cv_folds,
+ bool _use_1se_rule, bool _truncate_pruned_tree,
+ const float* _priors ) :
+ max_categories(_max_categories), max_depth(_max_depth),
+ min_sample_count(_min_sample_count), cv_folds (_cv_folds),
+ use_surrogates(_use_surrogates), use_1se_rule(_use_1se_rule),
+ truncate_pruned_tree(_truncate_pruned_tree),
+ regression_accuracy(_regression_accuracy),
+ priors(_priors)
+{}
CvDTree::CvDTree()
{