Inheritance diagram for LightGBM::GPUTreeLearner:
Public Member Functions | |
| GPUTreeLearner (const Config *tree_config) | |
 Public Member Functions inherited from LightGBM::SerialTreeLearner | |
| SerialTreeLearner (const Config *config) | |
| void | Init (const Dataset *train_data, bool is_constant_hessian) override |
| Initialize tree learner with training dataset. | |
| void | ResetTrainingData (const Dataset *train_data) override |
| void | ResetConfig (const Config *config) override |
| Reset tree configs. | |
| Tree * | Train (const score_t *gradients, const score_t *hessians, bool is_constant_hessian, Json &forced_split_json) override |
| training tree model on dataset | |
| Tree * | FitByExistingTree (const Tree *old_tree, const score_t *gradients, const score_t *hessians) const override |
| use a existing tree to fit the new gradients and hessians. | |
| Tree * | FitByExistingTree (const Tree *old_tree, const std::vector< int > &leaf_pred, const score_t *gradients, const score_t *hessians) override |
| void | SetBaggingData (const data_size_t *used_indices, data_size_t num_data) override |
| Set bagging data. | |
| void | AddPredictionToScore (const Tree *tree, double *out_score) const override |
| Using last trained tree to predict score then adding to out_score;. | |
| void | RenewTreeOutput (Tree *tree, const ObjectiveFunction *obj, const double *prediction, data_size_t total_num_data, const data_size_t *bag_indices, data_size_t bag_cnt) const override |
| void | RenewTreeOutput (Tree *tree, const ObjectiveFunction *obj, double prediction, data_size_t total_num_data, const data_size_t *bag_indices, data_size_t bag_cnt) const override |
| Public Member Functions inherited from LightGBM::TreeLearner | |
| virtual | ~TreeLearner () |
| virtual destructor | |
| TreeLearner & | operator= (const TreeLearner &)=delete |
| Disable copy. | |
| TreeLearner (const TreeLearner &)=delete | |
| Disable copy. | |
Additional Inherited Members | |
| Static Public Member Functions inherited from LightGBM::TreeLearner | |
| static TreeLearner * | CreateTreeLearner (const std::string &learner_type, const std::string &device_type, const Config *config) |
| Create object of tree learner. | |
| Protected Member Functions inherited from LightGBM::SerialTreeLearner | |
| virtual void | BeforeTrain () |
| Some initial works before training. | |
| virtual bool | BeforeFindBestSplit (const Tree *tree, int left_leaf, int right_leaf) |
| Some initial works before FindBestSplit. | |
| virtual void | FindBestSplits () |
| virtual void | ConstructHistograms (const std::vector< int8_t > &is_feature_used, bool use_subtract) |
| virtual void | FindBestSplitsFromHistograms (const std::vector< int8_t > &is_feature_used, bool use_subtract) |
| virtual void | Split (Tree *tree, int best_leaf, int *left_leaf, int *right_leaf) |
| Partition tree and data according best split. | |
| virtual int32_t | ForceSplits (Tree *tree, Json &forced_split_json, int *left_leaf, int *right_leaf, int *cur_depth, bool *aborted_last_force_split) |
| virtual data_size_t | GetGlobalDataCountInLeaf (int leaf_idx) const |
| Get the number of data in a leaf. | |
| Protected Attributes inherited from LightGBM::SerialTreeLearner | |
| data_size_t | num_data_ |
| number of data | |
| int | num_features_ |
| number of features | |
| const Dataset * | train_data_ |
| training data | |
| const score_t * | gradients_ |
| gradients of current iteration | |
| const score_t * | hessians_ |
| hessians of current iteration | |
| std::unique_ptr< DataPartition > | data_partition_ |
| training data partition on leaves | |
| Random | random_ |
| used for generate used features | |
| std::vector< int8_t > | is_feature_used_ |
| used for sub feature training, is_feature_used_[i] = false means don't used feature i | |
| FeatureHistogram * | parent_leaf_histogram_array_ |
| pointer to histograms array of parent of current leaves | |
| FeatureHistogram * | smaller_leaf_histogram_array_ |
| pointer to histograms array of smaller leaf | |
| FeatureHistogram * | larger_leaf_histogram_array_ |
| pointer to histograms array of larger leaf | |
| std::vector< SplitInfo > | best_split_per_leaf_ |
| store best split points for all leaves | |
| std::unique_ptr< LeafSplits > | smaller_leaf_splits_ |
| stores best thresholds for all feature for smaller leaf | |
| std::unique_ptr< LeafSplits > | larger_leaf_splits_ |
| stores best thresholds for all feature for larger leaf | |
| std::vector< int > | valid_feature_indices_ |
| std::vector< score_t > | ordered_gradients_ |
| gradients of current iteration, ordered for cache optimized | |
| std::vector< score_t > | ordered_hessians_ |
| hessians of current iteration, ordered for cache optimized | |
| std::vector< std::unique_ptr< OrderedBin > > | ordered_bins_ |
| Store ordered bin. | |
| bool | has_ordered_bin_ = false |
| True if has ordered bin. | |
| std::vector< char > | is_data_in_leaf_ |
| is_data_in_leaf_[i] != 0 means i-th data is marked | |
| HistogramPool | histogram_pool_ |
| used to cache historical histogram to speed up | |
| const Config * | config_ |
| config of tree learner | |
| int | num_threads_ |
| std::vector< int > | ordered_bin_indices_ |
| bool | is_constant_hessian_ |
The documentation for this class was generated from the following file:
- External/LightGBM_2.2.3/LightGBM-2.2.3/src/treelearner/gpu_tree_learner.h
