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Use DART tree weights when computing SHAPs (#5050)

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This PR fixes tree weights in dart being ignored when computing contributions.

* Fix ellpack page source link.
* Add tree weights to compute contribution.
This commit is contained in:
Kodi Arfer
2019-12-03 06:55:53 -05:00
committed by Jiaming Yuan
parent 64f4361b47
commit f2277e7106
12 changed files with 88 additions and 16 deletions
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3
include/xgboost/predictor.h
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@@ -149,6 +149,7 @@ class Predictor {
* \param [in,out] out_contribs The output feature contribs.
* \param model Model to make predictions from.
* \param ntree_limit (Optional) The ntree limit.
* \param tree_weights (Optional) Weights to multiply each tree by.
* \param approximate Use fast approximate algorithm.
* \param condition Condition on the condition_feature (0=no, -1=cond off, 1=cond on).
* \param condition_feature Feature to condition on (i.e. fix) during calculations.
@@ -158,6 +159,7 @@ class Predictor {
std::vector<bst_float>* out_contribs,
const gbm::GBTreeModel& model,
unsigned ntree_limit = 0,
std::vector<bst_float>* tree_weights = nullptr,
bool approximate = false,
int condition = 0,
unsigned condition_feature = 0) = 0;
@@ -166,6 +168,7 @@ class Predictor {
std::vector<bst_float>* out_contribs,
const gbm::GBTreeModel& model,
unsigned ntree_limit = 0,
std::vector<bst_float>* tree_weights = nullptr,
bool approximate = false) = 0;
/**