英文:
How to differentiate model types from xgboost XGBRFClassifier and XGBClassifier
问题
我正在构建一个支持xgboost中的XGBClassifier和XGBRFClassifier的模块。我想要在我的模块中区分它们，但我注意到：
from xgboost import XGBRFClassifier, XGBClassifier
xgbrf_model = XGBRFClassifier()
isinstance(xgbrf_model, XGBClassifier) # True
这显然不应该是真的。我想坚持使用isinstance，而不是尝试：
type(xgbrf_model) == XGBClassifier # False
英文:
I'm building a module that supports both XGBClassifier and XGBRFClassifier from xgboost. I want to differentiate them in my module but I noticed that:
from xgboost import XGBRFClassifier, XGBClassifier
xgbrf_model = XGBRFClassifier()
isinstance(xgbrf_model, XGBClassifier) # True
This should obviously not be true. I want to stick to isinstance and not try:
type(xgbrf_model) == XGBClassifier # False
答案1
得分: 1
如下翻译：
截止到XGBoost版本v1.7.3，XGBRFClassifier类是XGBClassifier类的直接子类：
https://github.com/dmlc/xgboost/blob/v1.7.3/python-package/xgboost/sklearn.py#L1627
因此，这个isinstance检查正确地评估为True。
最佳做法是从更具体的类检查到不太具体的类。也就是说，首先检查XGBRFClassifier，如果评估为False，然后才检查XGBClassifier。
英文:
> This should obviously not be true ..isinstance(XGBRFClassifier(), XGBClassifier)
As of XGBoost version v1.7.3, the XGBRFClassifier class is a direct subclass of the XGBClassifier class:
https://github.com/dmlc/xgboost/blob/v1.7.3/python-package/xgboost/sklearn.py#L1627
Therefore, this isinstance check correctly evaluates to True.
Your best bet is to perform checks from more specific classes to less specific classes. That is, check for XGBRFClassifier first, and if that evaluates to False, only then check for XGBClassifier.
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