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[doc] Clarification for feature importance. (#8151)

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Jiaming Yuan 2022-08-11 00:30:42 +08:00 committed by GitHub
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1 changed files with 6 additions and 2 deletions
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python-package/xgboost/sklearn.py
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@ -1259,8 +1259,12 @@ class XGBModel(XGBModelBase):
@property @property
def feature_importances_(self) -> np.ndarray: def feature_importances_(self) -> np.ndarray:
""" """Feature importances property, return depends on `importance_type`
Feature importances property, return depends on `importance_type` parameter. parameter. When model trained with multi-class/multi-label/multi-target dataset,
the feature importance is "averaged" over all targets. The "average" is defined
based on the importance type. For instance, if the importance type is
"total_gain", then the score is sum of loss change for each split from all
trees.
Returns Returns
------- -------