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

Deprecate reg:linear' in favor of reg:squarederror'. (#4267)

Browse Source 
* Deprecate `reg:linear' in favor of `reg:squarederror'.
* Replace the use of `reg:linear'.
* Replace the use of `silent`.
This commit is contained in:
Jiaming Yuan
2019-03-17 17:55:04 +08:00
committed by GitHub
parent cf8d5b9b76
commit 29a1356669
34 changed files with 210 additions and 193 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
tests/python/test_with_pandas.py
View File

@@ -120,7 +120,7 @@ class TestPandas(unittest.TestCase):
def test_cv_as_pandas(self):
dm = xgb.DMatrix(dpath + 'agaricus.txt.train')
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
params = {'max_depth': 2, 'eta': 1, 'verbosity': 0,
'objective': 'binary:logistic'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10)
@@ -143,19 +143,19 @@ class TestPandas(unittest.TestCase):
u'train-error-mean', u'train-error-std'])
assert cv.columns.equals(exp)
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
params = {'max_depth': 2, 'eta': 1, 'verbosity': 0,
'objective': 'binary:logistic', 'eval_metric': 'auc'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True)
assert 'eval_metric' in params
assert 'auc' in cv.columns[0]
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
params = {'max_depth': 2, 'eta': 1, 'verbosity': 0,
'objective': 'binary:logistic', 'eval_metric': ['auc']}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True)
assert 'eval_metric' in params
assert 'auc' in cv.columns[0]
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
params = {'max_depth': 2, 'eta': 1, 'verbosity': 0,
'objective': 'binary:logistic', 'eval_metric': ['auc']}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, early_stopping_rounds=1)
@@ -163,19 +163,19 @@ class TestPandas(unittest.TestCase):
assert 'auc' in cv.columns[0]
assert cv.shape[0] < 10
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
params = {'max_depth': 2, 'eta': 1, 'verbosity': 0,
'objective': 'binary:logistic'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, metrics='auc')
assert 'auc' in cv.columns[0]
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
params = {'max_depth': 2, 'eta': 1, 'verbosity': 0,
'objective': 'binary:logistic'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, metrics=['auc'])
assert 'auc' in cv.columns[0]
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
params = {'max_depth': 2, 'eta': 1, 'verbosity': 0,
'objective': 'binary:logistic', 'eval_metric': ['auc']}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, metrics='error')