Inheritance diagram for LightGBM::GBDTBase:
Public Member Functions | |
| virtual double | GetLeafValue (int tree_idx, int leaf_idx) const =0 |
| virtual void | SetLeafValue (int tree_idx, int leaf_idx, double val)=0 |
 Public Member Functions inherited from LightGBM::Boosting | |
| virtual | ~Boosting () |
| virtual destructor | |
| virtual void | Init (const Config *config, const Dataset *train_data, const ObjectiveFunction *objective_function, const std::vector< const Metric * > &training_metrics)=0 |
| Initialization logic. | |
| virtual void | MergeFrom (const Boosting *other)=0 |
| Merge model from other boosting object Will insert to the front of current boosting object. | |
| virtual void | ShuffleModels (int start_iter, int end_iter)=0 |
| Shuffle Existing Models. | |
| virtual void | ResetTrainingData (const Dataset *train_data, const ObjectiveFunction *objective_function, const std::vector< const Metric * > &training_metrics)=0 |
| virtual void | ResetConfig (const Config *config)=0 |
| virtual void | AddValidDataset (const Dataset *valid_data, const std::vector< const Metric * > &valid_metrics)=0 |
| Add a validation data. | |
| virtual void | Train (int snapshot_freq, const std::string &model_output_path)=0 |
| virtual void | RefitTree (const std::vector< std::vector< int > > &tree_leaf_prediction)=0 |
| Update the tree output by new training data. | |
| virtual bool | TrainOneIter (const score_t *gradients, const score_t *hessians)=0 |
| Training logic. | |
| virtual void | RollbackOneIter ()=0 |
| Rollback one iteration. | |
| virtual int | GetCurrentIteration () const =0 |
| return current iteration | |
| virtual std::vector< double > | GetEvalAt (int data_idx) const =0 |
| Get evaluation result at data_idx data. | |
| virtual const double * | GetTrainingScore (int64_t *out_len)=0 |
| Get current training score. | |
| virtual int64_t | GetNumPredictAt (int data_idx) const =0 |
| Get prediction result at data_idx data. | |
| virtual void | GetPredictAt (int data_idx, double *result, int64_t *out_len)=0 |
| Get prediction result at data_idx data. | |
| virtual int | NumPredictOneRow (int num_iteration, bool is_pred_leaf, bool is_pred_contrib) const =0 |
| virtual void | PredictRaw (const double *features, double *output, const PredictionEarlyStopInstance *early_stop) const =0 |
| Prediction for one record, not sigmoid transform. | |
| virtual void | PredictRawByMap (const std::unordered_map< int, double > &features, double *output, const PredictionEarlyStopInstance *early_stop) const =0 |
| virtual void | Predict (const double *features, double *output, const PredictionEarlyStopInstance *early_stop) const =0 |
| Prediction for one record, sigmoid transformation will be used if needed. | |
| virtual void | PredictByMap (const std::unordered_map< int, double > &features, double *output, const PredictionEarlyStopInstance *early_stop) const =0 |
| virtual void | PredictLeafIndex (const double *features, double *output) const =0 |
| Prediction for one record with leaf index. | |
| virtual void | PredictLeafIndexByMap (const std::unordered_map< int, double > &features, double *output) const =0 |
| virtual void | PredictContrib (const double *features, double *output, const PredictionEarlyStopInstance *early_stop) const =0 |
| Feature contributions for the model's prediction of one record. | |
| virtual std::string | DumpModel (int start_iteration, int num_iteration) const =0 |
| Dump model to json format string. | |
| virtual std::string | ModelToIfElse (int num_iteration) const =0 |
| Translate model to if-else statement. | |
| virtual bool | SaveModelToIfElse (int num_iteration, const char *filename) const =0 |
| Translate model to if-else statement. | |
| virtual bool | SaveModelToFile (int start_iteration, int num_iterations, const char *filename) const =0 |
| Save model to file. | |
| std::string | SaveModelToString (int num_iterations) |
| Save model to string. | |
| virtual std::string | SaveModelToString (int start_iteration, int num_iterations) const =0 |
| bool | LoadModelFromString (std::string str) |
| Restore from a serialized string. | |
| virtual bool | LoadModelFromString (const char *buffer, size_t len)=0 |
| virtual std::vector< double > | FeatureImportance (int num_iteration, int importance_type) const =0 |
| Calculate feature importances. | |
| virtual int | MaxFeatureIdx () const =0 |
| Get max feature index of this model. | |
| virtual std::vector< std::string > | FeatureNames () const =0 |
| Get feature names of this model. | |
| virtual int | LabelIdx () const =0 |
| Get index of label column. | |
| virtual int | NumberOfTotalModel () const =0 |
| Get number of weak sub-models. | |
| virtual int | NumModelPerIteration () const =0 |
| Get number of models per iteration. | |
| virtual int | NumberOfClasses () const =0 |
| Get number of classes. | |
| virtual bool | NeedAccuratePrediction () const =0 |
| The prediction should be accurate or not. True will disable early stopping for prediction. | |
| virtual void | InitPredict (int num_iteration, bool is_pred_contrib)=0 |
| Initial work for the prediction. | |
| virtual const char * | SubModelName () const =0 |
| Name of submodel. | |
| Boosting & | operator= (const Boosting &)=delete |
| Disable copy. | |
| Boosting (const Boosting &)=delete | |
| Disable copy. | |
Additional Inherited Members | |
| Static Public Member Functions inherited from LightGBM::Boosting | |
| static bool | LoadFileToBoosting (Boosting *boosting, const char *filename) |
| static Boosting * | CreateBoosting (const std::string &type, const char *filename) |
| Create boosting object. | |
The documentation for this class was generated from the following file:
- External/LightGBM_2.2.3/LightGBM-2.2.3/include/LightGBM/boosting.h
