90                      int cfg_max_depth               = -1,
 
   91                      int cfg_max_leaves              = -1,
 
   92                      float cfg_max_features          = 1.0f,
 
   93                      int cfg_max_n_bins              = 128,
 
   94                      int cfg_min_samples_leaf        = 1,
 
   95                      int cfg_min_samples_split       = 2,
 
   96                      float cfg_min_impurity_decrease = 0.0f,
 
   98                      int cfg_max_batch_size          = 4096);
 
  100 template <
class T, 
class L>
 
  118 template <
class T, 
class L>
 
  128 template <
class T, 
class L>
 
  138 template <
class T, 
class L>
 
Definition: params.hpp:34
 
TreeMetaDataNode< double, double > TreeRegressorD
Definition: decisiontree.hpp:144
 
void set_tree_params(DecisionTreeParams ¶ms, int cfg_max_depth=-1, int cfg_max_leaves=-1, float cfg_max_features=1.0f, int cfg_max_n_bins=128, int cfg_min_samples_leaf=1, int cfg_min_samples_split=2, float cfg_min_impurity_decrease=0.0f, CRITERION cfg_split_criterion=CRITERION_END, int cfg_max_batch_size=4096)
Set all DecisionTreeParams members.
 
std::string get_tree_text(const TreeMetaDataNode< T, L > *tree)
Obtain detailed tree information.
 
std::string get_tree_json(const TreeMetaDataNode< T, L > *tree)
Export tree as a JSON string.
 
std::string get_tree_summary_text(const TreeMetaDataNode< T, L > *tree)
Obtain high-level tree information.
 
TreeMetaDataNode< double, int > TreeClassifierD
Definition: decisiontree.hpp:142
 
TreeMetaDataNode< float, float > TreeRegressorF
Definition: decisiontree.hpp:143
 
TreeMetaDataNode< float, int > TreeClassifierF
Definition: decisiontree.hpp:141
 
Definition: dbscan.hpp:29
 
CRITERION
Definition: algo_helper.h:20
 
@ CRITERION_END
Definition: algo_helper.h:28
 
Definition: decisiontree.hpp:29
 
int max_batch_size
Definition: decisiontree.hpp:68
 
int max_n_bins
Definition: decisiontree.hpp:45
 
CRITERION split_criterion
Definition: decisiontree.hpp:57
 
float max_features
Definition: decisiontree.hpp:41
 
int min_samples_leaf
Definition: decisiontree.hpp:49
 
int max_depth
Definition: decisiontree.hpp:33
 
float min_impurity_decrease
Definition: decisiontree.hpp:62
 
int min_samples_split
Definition: decisiontree.hpp:53
 
int max_leaves
Definition: decisiontree.hpp:37