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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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2
tests/python/test_ranking.py
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@@ -135,7 +135,7 @@ class TestRanking(unittest.TestCase):
# specify validations set to watch performance
watchlist = [(self.dtest, 'eval'), (self.dtrain, 'train')]
bst = xgboost.train(self.params, self.dtrain, num_boost_round=2500,
early_stopping_rounds=10, evals=watchlist)
early_stopping_rounds=10, evals=watchlist)
assert bst.best_score > 0.98
def test_cv(self):