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Fix coef_ and intercept_ signature to be compatible with sklearn.RFECV (#3873)

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* Fix coef_ and intercept_ signature to be compatible with sklearn.RFECV

* Fix lint

* Fix lint
This commit is contained in:
Philip Hyunsu Cho
2018-11-08 19:41:35 -08:00
committed by GitHub
parent 19ee0a3579
commit ad6e0d55f1
2 changed files with 45 additions and 4 deletions
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16
python-package/xgboost/sklearn.py
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@@ -535,13 +535,21 @@ class XGBModel(XGBModelBase):
Returns
-------
coef_ : array of shape ``[n_features]``
coef_ : array of shape ``[n_features]`` or ``[n_classes, n_features]``
"""
if self.booster != 'gblinear':
raise AttributeError('Coefficients are not defined for Booster type {}'
.format(self.booster))
b = self.get_booster()
return 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:
if n_classes > 2:
assert len(coef.shape) == 1
assert coef.shape[0] % n_classes == 0
coef = coef.reshape((n_classes, -1))
return coef
@property
def intercept_(self):
@@ -556,13 +564,13 @@ class XGBModel(XGBModelBase):
Returns
-------
intercept_ : array of shape ``[n_features]``
intercept_ : array of shape ``(1,)`` or ``[n_classes]``
"""
if self.booster != 'gblinear':
raise AttributeError('Intercept (bias) is not defined for Booster type {}'
.format(self.booster))
b = self.get_booster()
return json.loads(b.get_dump(dump_format='json')[0])['bias']
return np.array(json.loads(b.get_dump(dump_format='json')[0])['bias'])
class XGBClassifier(XGBModel, XGBClassifierBase):