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[Breaking] Don't drop trees during DART prediction by default (#5115)

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* Simplify DropTrees calling logic

* Add `training` parameter for prediction method.

* [Breaking]: Add `training` to C API.

* Change for R and Python custom objective.

* Correct comment.

Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
This commit is contained in:
Kodi Arfer
2020-01-13 08:48:30 -05:00
committed by Jiaming Yuan
parent 7b65698187
commit f100b8d878
23 changed files with 214 additions and 140 deletions
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jvm-packages/xgboost4j/src/native/xgboost4j.cpp
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@@ -556,7 +556,8 @@ JNIEXPORT jint JNICALL Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterPredict
DMatrixHandle dmat = (DMatrixHandle) jdmat;
bst_ulong len;
float *result;
int ret = XGBoosterPredict(handle, dmat, joption_mask, (unsigned int) jntree_limit, &len, (const float **) &result);
int ret = XGBoosterPredict(handle, dmat, joption_mask, (unsigned int) jntree_limit, 0,
&len, (const float **) &result);
if (len) {
jsize jlen = (jsize) len;
jfloatArray jarray = jenv->NewFloatArray(jlen);