randomforest.hpp File Reference

#include <cuml/common/logger.hpp>
#include <cuml/ensemble/treelite_defs.hpp>
#include <cuml/tree/decisiontree.hpp>
#include <map>
#include <memory>

Include dependency graph for randomforest.hpp:

Go to the source code of this file.

Classes
struct	ML::RF_metrics
struct	ML::RF_params
struct	ML::RandomForestMetaData< T, L >

Namespaces
	raft
	ML

Typedefs
typedef RandomForestMetaData< float, int >	ML::RandomForestClassifierF
typedef RandomForestMetaData< double, int >	ML::RandomForestClassifierD
typedef RandomForestMetaData< float, float >	ML::RandomForestRegressorF
typedef RandomForestMetaData< double, double >	ML::RandomForestRegressorD

Enumerations
enum	ML::RF_type { ML::CLASSIFICATION , ML::REGRESSION }
enum	ML::task_category { ML::REGRESSION_MODEL = 1 , ML::CLASSIFICATION_MODEL = 2 }

Functions
RF_metrics	ML::set_all_rf_metrics (RF_type rf_type, float accuracy, double mean_abs_error, double mean_squared_error, double median_abs_error)
RF_metrics	ML::set_rf_metrics_classification (float accuracy)
RF_metrics	ML::set_rf_metrics_regression (double mean_abs_error, double mean_squared_error, double median_abs_error)
void	ML::print (const RF_metrics rf_metrics)
void	ML::preprocess_labels (int n_rows, std::vector< int > &labels, std::map< int, int > &labels_map, int verbosity=CUML_LEVEL_INFO)
void	ML::postprocess_labels (int n_rows, std::vector< int > &labels, std::map< int, int > &labels_map, int verbosity=CUML_LEVEL_INFO)
template<class T , class L >
void	ML::delete_rf_metadata (RandomForestMetaData< T, L > *forest)
template<class T , class L >
std::string	ML::get_rf_summary_text (const RandomForestMetaData< T, L > *forest)
template<class T , class L >
std::string	ML::get_rf_detailed_text (const RandomForestMetaData< T, L > *forest)
template<class T , class L >
std::string	ML::get_rf_json (const RandomForestMetaData< T, L > *forest)
template<class T , class L >
void	ML::build_treelite_forest (TreeliteModelHandle *model, const RandomForestMetaData< T, L > *forest, int num_features)
TreeliteModelHandle	ML::concatenate_trees (std::vector< TreeliteModelHandle > treelite_handles)
void	ML::fit (const raft::handle_t &user_handle, RandomForestClassifierF *&forest, float *input, int n_rows, int n_cols, int *labels, int n_unique_labels, RF_params rf_params, int verbosity=CUML_LEVEL_INFO)
void	ML::fit (const raft::handle_t &user_handle, RandomForestClassifierD *&forest, double *input, int n_rows, int n_cols, int *labels, int n_unique_labels, RF_params rf_params, int verbosity=CUML_LEVEL_INFO)
void	ML::predict (const raft::handle_t &user_handle, const RandomForestClassifierF *forest, const float *input, int n_rows, int n_cols, int *predictions, int verbosity=CUML_LEVEL_INFO)
void	ML::predict (const raft::handle_t &user_handle, const RandomForestClassifierD *forest, const double *input, int n_rows, int n_cols, int *predictions, int verbosity=CUML_LEVEL_INFO)
RF_metrics	ML::score (const raft::handle_t &user_handle, const RandomForestClassifierF *forest, const int *ref_labels, int n_rows, const int *predictions, int verbosity=CUML_LEVEL_INFO)
RF_metrics	ML::score (const raft::handle_t &user_handle, const RandomForestClassifierD *forest, const int *ref_labels, int n_rows, const int *predictions, int verbosity=CUML_LEVEL_INFO)
RF_params	ML::set_rf_params (int max_depth, int max_leaves, float max_features, int max_n_bins, int min_samples_leaf, int min_samples_split, float min_impurity_decrease, bool bootstrap, int n_trees, float max_samples, uint64_t seed, CRITERION split_criterion, int cfg_n_streams, int max_batch_size)
void	ML::fit (const raft::handle_t &user_handle, RandomForestRegressorF *&forest, float *input, int n_rows, int n_cols, float *labels, RF_params rf_params, int verbosity=CUML_LEVEL_INFO)
void	ML::fit (const raft::handle_t &user_handle, RandomForestRegressorD *&forest, double *input, int n_rows, int n_cols, double *labels, RF_params rf_params, int verbosity=CUML_LEVEL_INFO)
void	ML::predict (const raft::handle_t &user_handle, const RandomForestRegressorF *forest, const float *input, int n_rows, int n_cols, float *predictions, int verbosity=CUML_LEVEL_INFO)
void	ML::predict (const raft::handle_t &user_handle, const RandomForestRegressorD *forest, const double *input, int n_rows, int n_cols, double *predictions, int verbosity=CUML_LEVEL_INFO)
RF_metrics	ML::score (const raft::handle_t &user_handle, const RandomForestRegressorF *forest, const float *ref_labels, int n_rows, const float *predictions, int verbosity=CUML_LEVEL_INFO)
RF_metrics	ML::score (const raft::handle_t &user_handle, const RandomForestRegressorD *forest, const double *ref_labels, int n_rows, const double *predictions, int verbosity=CUML_LEVEL_INFO)