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Trunk: moved contructors implementations from .hpp to .cpp

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This commit is contained in:
Ilya Lysenkov 2011-06-24 12:25:52 +00:00
parent 2edf764eee
commit 2c958b2598
3 changed files with 49 additions and 37 deletions
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49
modules/ml/include/opencv2/ml/ml.hpp
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@ -744,23 +744,12 @@ struct CV_EXPORTS_W_MAP CvDTreeParams
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 );
};
@ -1016,26 +1005,12 @@ struct CV_EXPORTS_W_MAP CvRTParams : public CvDTreeParams
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 );
};

20
modules/ml/src/rtrees.cpp
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@ -190,6 +190,26 @@ void CvForestTree::read( CvFileStorage* _fs, CvFileNode* _node,
//////////////////////////////////////////////////////////////////////////////////////////
// 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()
{

17
modules/ml/src/tree.cpp
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@ -1466,6 +1466,23 @@ void CvDTreeTrainData::read_params( CvFileStorage* fs, CvFileNode* node )
}
/////////////////////// 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()
{