Performs prediction on individual training instances or batches of instances for GBTree. More...
#include <predictor.h>
Inheritance diagram for xgboost::Predictor:
Public Member Functions | |
| Predictor (Context const *ctx) | |
| virtual void | Configure (Args const &) |
| Configure and register input matrices in prediction cache. | |
| void | InitOutPredictions (const MetaInfo &info, HostDeviceVector< bst_float > *out_predt, const gbm::GBTreeModel &model) const |
| Initialize output prediction. | |
| virtual void | PredictBatch (DMatrix *dmat, PredictionCacheEntry *out_preds, const gbm::GBTreeModel &model, uint32_t tree_begin, uint32_t tree_end=0) const =0 |
| Generate batch predictions for a given feature matrix. | |
| virtual bool | InplacePredict (std::shared_ptr< DMatrix > p_fmat, const gbm::GBTreeModel &model, float missing, PredictionCacheEntry *out_preds, uint32_t tree_begin=0, uint32_t tree_end=0) const =0 |
| Inplace prediction. | |
| virtual void | PredictInstance (const SparsePage::Inst &inst, std::vector< bst_float > *out_preds, const gbm::GBTreeModel &model, unsigned tree_end=0, bool is_column_split=false) const =0 |
| online prediction function, predict score for one instance at a time NOTE: use the batch prediction interface if possible, batch prediction is usually more efficient than online prediction This function is NOT threadsafe, make sure you only call from one thread. | |
| virtual void | PredictLeaf (DMatrix *dmat, HostDeviceVector< bst_float > *out_preds, const gbm::GBTreeModel &model, unsigned tree_end=0) const =0 |
| predict the leaf index of each tree, the output will be nsample * ntree vector this is only valid in gbtree predictor. | |
| virtual void | PredictContribution (DMatrix *dmat, HostDeviceVector< bst_float > *out_contribs, const gbm::GBTreeModel &model, unsigned tree_end=0, std::vector< bst_float > const *tree_weights=nullptr, bool approximate=false, int condition=0, unsigned condition_feature=0) const =0 |
| feature contributions to individual predictions; the output will be a vector of length (nfeats + 1) * num_output_group * nsample, arranged in that order. | |
| virtual void | PredictInteractionContributions (DMatrix *dmat, HostDeviceVector< bst_float > *out_contribs, const gbm::GBTreeModel &model, unsigned tree_end=0, std::vector< bst_float > const *tree_weights=nullptr, bool approximate=false) const =0 |
Static Public Member Functions | |
| static Predictor * | Create (std::string const &name, Context const *ctx) |
| Creates a new Predictor*. | |
Protected Attributes | |
| Context const * | ctx_ |
Detailed Description
Performs prediction on individual training instances or batches of instances for GBTree.
Prediction functions all take a GBTreeModel and a DMatrix as input and output a vector of predictions. The predictor does not modify any state of the model itself.
Member Function Documentation
◆ Configure()
|
virtual |
Configure and register input matrices in prediction cache.
- Parameters
-
cfg The configuration.
◆ Create()
Creates a new Predictor*.
- Parameters
-
name Name of the predictor. ctx Pointer to runtime parameters.
◆ InitOutPredictions()
| void xgboost::Predictor::InitOutPredictions | ( | const MetaInfo & | info, |
| HostDeviceVector< bst_float > * | out_predt, | ||
| const gbm::GBTreeModel & | model | ||
| ) | const |
Initialize output prediction.
- Parameters
-
info Meta info for the DMatrix object used for prediction. out_predt Prediction vector to be initialized. model Tree model used for prediction.
◆ InplacePredict()
|
pure virtual |
Inplace prediction.
- Parameters
-
p_fmat A proxy DMatrix that contains the data and related meta info. model The model to predict from. missing Missing value in the data. [in,out] out_preds The output preds. tree_begin (Optional) Beginning of boosted trees used for prediction. tree_end (Optional) End of booster trees. 0 means do not limit trees.
- Returns
- True if the data can be handled by current predictor, false otherwise.
◆ PredictBatch()
|
pure virtual |
Generate batch predictions for a given feature matrix.
May use cached predictions if available instead of calculating from scratch.
- Parameters
-
[in,out] dmat Feature matrix. [in,out] out_preds The output preds. model The model to predict from. tree_begin The tree begin index. tree_end The tree end index.
Implemented in xgboost::predictor::CPUPredictor.
◆ PredictContribution()
|
pure virtual |
feature contributions to individual predictions; the output will be a vector of length (nfeats + 1) * num_output_group * nsample, arranged in that order.
- Parameters
-
[in,out] dmat The input feature matrix. [in,out] out_contribs The output feature contribs. model Model to make predictions from. tree_end The tree end index. tree_weights (Optional) Weights to multiply each tree by. approximate Use fast approximate algorithm. condition Condition on the condition_feature (0=no, -1=cond off, 1=cond on). condition_feature Feature to condition on (i.e. fix) during calculations.
◆ PredictInstance()
|
pure virtual |
online prediction function, predict score for one instance at a time NOTE: use the batch prediction interface if possible, batch prediction is usually more efficient than online prediction This function is NOT threadsafe, make sure you only call from one thread.
- Parameters
-
inst The instance to predict. [in,out] out_preds The output preds. model The model to predict from tree_end (Optional) The tree end index. is_column_split (Optional) If the data is split column-wise.
Implemented in xgboost::predictor::CPUPredictor.
◆ PredictLeaf()
|
pure virtual |
predict the leaf index of each tree, the output will be nsample * ntree vector this is only valid in gbtree predictor.
- Parameters
-
[in,out] dmat The input feature matrix. [in,out] out_preds The output preds. model Model to make predictions from. tree_end (Optional) The tree end index.
Implemented in xgboost::predictor::CPUPredictor.
The documentation for this class was generated from the following files:
- External/xgboost/include/xgboost/predictor.h
- External/xgboost/src/predictor/predictor.cc
