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Remove output_margin from XGBClassifier.predict_proba argument list. (#3343)

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Yanbo Liang 2018-05-28 10:30:21 -07:00 committed by Philip Hyunsu Cho
parent 34aeee2961
commit b018ef104f
1 changed files with 1 additions and 4 deletions
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python-package/xgboost/sklearn.py
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@ -564,7 +564,7 @@ class XGBClassifier(XGBModel, XGBClassifierBase):
column_indexes[class_probs > 0.5] = 1 column_indexes[class_probs > 0.5] = 1
return self._le.inverse_transform(column_indexes) return self._le.inverse_transform(column_indexes)
def predict_proba(self, data, output_margin=False, ntree_limit=0): def predict_proba(self, data, ntree_limit=0):
""" """
Predict the probability of each `data` example being of a given class. Predict the probability of each `data` example being of a given class.
NOTE: This function is not thread safe. NOTE: This function is not thread safe.
@ -575,8 +575,6 @@ class XGBClassifier(XGBModel, XGBClassifierBase):
---------- ----------
data : DMatrix data : DMatrix
The dmatrix storing the input. The dmatrix storing the input.
output_margin : bool
Whether to output the raw untransformed margin value.
ntree_limit : int ntree_limit : int
Limit number of trees in the prediction; defaults to 0 (use all trees). Limit number of trees in the prediction; defaults to 0 (use all trees).
Returns Returns
@ -586,7 +584,6 @@ class XGBClassifier(XGBModel, XGBClassifierBase):
""" """
test_dmatrix = DMatrix(data, missing=self.missing, nthread=self.n_jobs) test_dmatrix = DMatrix(data, missing=self.missing, nthread=self.n_jobs)
class_probs = self.get_booster().predict(test_dmatrix, class_probs = self.get_booster().predict(test_dmatrix,
output_margin=output_margin,
ntree_limit=ntree_limit) ntree_limit=ntree_limit)
if self.objective == "multi:softprob": if self.objective == "multi:softprob":
return class_probs return class_probs