Feature parallel learning algorithm. Different machine will find best split on different features, then sync global best split It is recommonded used when data is small or #feature is large. More...
#include <parallel_tree_learner.h>
Inheritance diagram for LightGBM::FeatureParallelTreeLearner< TREELEARNER_T >:
Public Member Functions | |
| FeatureParallelTreeLearner (const Config *config) | |
| void | Init (const Dataset *train_data, bool is_constant_hessian) override |
Protected Member Functions | |
| void | BeforeTrain () override |
| void | FindBestSplitsFromHistograms (const std::vector< int8_t > &is_feature_used, bool use_subtract) override |
Detailed Description
template<typename TREELEARNER_T>
class LightGBM::FeatureParallelTreeLearner< TREELEARNER_T >
class LightGBM::FeatureParallelTreeLearner< TREELEARNER_T >
Feature parallel learning algorithm. Different machine will find best split on different features, then sync global best split It is recommonded used when data is small or #feature is large.
The documentation for this class was generated from the following files:
- External/LightGBM_2.2.3/LightGBM-2.2.3/src/treelearner/parallel_tree_learner.h
- External/LightGBM_2.2.3/LightGBM-2.2.3/src/treelearner/feature_parallel_tree_learner.cpp
