Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[R] Fix global feature importance and predict with 1 sample. (#7394)

Browse Source 
* [R] Fix global feature importance.

* Add implementation for tree index.  The parameter is not documented in C API since we
should work on porting the model slicing to R instead of supporting more use of tree
index.

* Fix the difference between "gain" and "total_gain".

* debug.

* Fix prediction.
This commit is contained in:
Jiaming Yuan
2021-11-05 10:07:00 +08:00
committed by GitHub
parent 48aff0eabd
commit c968217ca8
11 changed files with 119 additions and 49 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
include/xgboost/gbm.h
View File

@@ -182,9 +182,10 @@ class GradientBooster : public Model, public Configurable {
bool with_stats,
std::string format) const = 0;
virtual void FeatureScore(std::string const &importance_type,
std::vector<bst_feature_t> *features,
std::vector<float> *scores) const = 0;
virtual void FeatureScore(std::string const& importance_type,
common::Span<int32_t const> trees,
std::vector<bst_feature_t>* features,
std::vector<float>* scores) const = 0;
/*!
* \brief Whether the current booster uses GPU.
*/

7
include/xgboost/learner.h
View File

@@ -156,9 +156,10 @@ class Learner : public Model, public Configurable, public dmlc::Serializable {
/*!
* \brief Calculate feature score. See doc in C API for outputs.
*/
virtual void CalcFeatureScore(std::string const &importance_type,
std::vector<bst_feature_t> *features,
std::vector<float> *scores) = 0;
virtual void CalcFeatureScore(std::string const& importance_type,
common::Span<int32_t const> trees,
std::vector<bst_feature_t>* features,
std::vector<float>* scores) = 0;
/*
* \brief Get number of boosted rounds from gradient booster.