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

Fix checking booster. (#5505)

Browse Source 
* Use `get_params()` instead of `getattr` intrinsic.
This commit is contained in:
Jiaming Yuan
2020-04-10 12:21:21 +08:00
committed by GitHub
parent 6671b42dd4
commit dc2950fd90
2 changed files with 28 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
python-package/xgboost/sklearn.py
View File

@@ -307,7 +307,7 @@ class XGBModel(XGBModelBase):
np.iinfo(np.int32).max)
def parse_parameter(value):
for t in (int, float):
for t in (int, float, str):
try:
ret = t(value)
return ret
@@ -678,10 +678,10 @@ class XGBModel(XGBModelBase):
feature_importances_ : array of shape ``[n_features]``
"""
if getattr(self, 'booster', None) is not None and self.booster not in {
'gbtree', 'dart'}:
raise AttributeError('Feature importance is not defined for Booster type {}'
.format(self.booster))
if self.get_params()['booster'] not in {'gbtree', 'dart'}:
raise AttributeError(
'Feature importance is not defined for Booster type {}'
.format(self.booster))
b = self.get_booster()
score = b.get_score(importance_type=self.importance_type)
all_features = [score.get(f, 0.) for f in b.feature_names]
@@ -703,11 +703,13 @@ class XGBModel(XGBModelBase):
-------
coef_ : array of shape ``[n_features]`` or ``[n_classes, n_features]``
"""
if getattr(self, 'booster', None) is not None and self.booster != 'gblinear':
raise AttributeError('Coefficients are not defined for Booster type {}'
.format(self.booster))
if self.get_params()['booster'] != 'gblinear':
raise AttributeError(
'Coefficients are not defined for Booster type {}'
.format(self.booster))
b = self.get_booster()
coef = np.array(json.loads(b.get_dump(dump_format='json')[0])['weight'])
coef = np.array(json.loads(
b.get_dump(dump_format='json')[0])['weight'])
# Logic for multiclass classification
n_classes = getattr(self, 'n_classes_', None)
if n_classes is not None:
@@ -732,9 +734,10 @@ class XGBModel(XGBModelBase):
-------
intercept_ : array of shape ``(1,)`` or ``[n_classes]``
"""
if getattr(self, 'booster', None) is not None and self.booster != 'gblinear':
raise AttributeError('Intercept (bias) is not defined for Booster type {}'
.format(self.booster))
if self.get_params()['booster'] != 'gblinear':
raise AttributeError(
'Intercept (bias) is not defined for Booster type {}'
.format(self.booster))
b = self.get_booster()
return np.array(json.loads(b.get_dump(dump_format='json')[0])['bias'])