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

Move num_parallel_tree to model parameter. (#7751)

Browse Source 
The size of forest should be a property of model itself instead of a training
hyper-parameter.
This commit is contained in:
Jiaming Yuan
2022-03-29 02:32:42 +08:00
committed by GitHub
parent 8b3ecfca25
commit 3c9b04460a
11 changed files with 158 additions and 101 deletions
Download Patch File Download Diff File Expand all files Collapse all files

18
tests/python/test_with_sklearn.py
View File

@@ -329,21 +329,27 @@ def test_select_feature():
def test_num_parallel_tree():
from sklearn.datasets import fetch_california_housing
reg = xgb.XGBRegressor(n_estimators=4, num_parallel_tree=4,
tree_method='hist')
reg = xgb.XGBRegressor(n_estimators=4, num_parallel_tree=4, tree_method="hist")
X, y = fetch_california_housing(return_X_y=True)
bst = reg.fit(X=X, y=y)
dump = bst.get_booster().get_dump(dump_format='json')
dump = bst.get_booster().get_dump(dump_format="json")
assert len(dump) == 16
reg = xgb.XGBRFRegressor(n_estimators=4)
bst = reg.fit(X=X, y=y)
dump = bst.get_booster().get_dump(dump_format='json')
dump = bst.get_booster().get_dump(dump_format="json")
assert len(dump) == 4
config = json.loads(bst.get_booster().save_config())
assert int(config['learner']['gradient_booster']['gbtree_train_param'][
'num_parallel_tree']) == 4
assert (
int(
config["learner"]["gradient_booster"]["gbtree_model_param"][
"num_parallel_tree"
]
)
== 4
)
def test_calif_housing_regression():