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abess-team / abess

Fast Best-Subset Selection Library
https://abess.readthedocs.io/
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Use same keyword arguments for sample weight as sklearn #454

Closed lindnemi closed 2 years ago

lindnemi commented 2 years ago

First of all: Thank you for the great package, it has been very helpful. Now to my suggestion:

Abess uses weight https://abess.readthedocs.io/en/latest/Python-package/linear/Logistic.html?highlight=score#abess.linear.LogisticRegression.fit Sklearn uses sample_weight https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html#sklearn.linear_model.LogisticRegression.fit

I'm using both in a project and it would be helpful if abess followed the sklearn convention.

Mamba413 commented 2 years ago

An excellent suggestion! We going to modify our API in the future version.

Mamba413 commented 2 years ago

@lindnemi , we have used the same keyword arguments for sample_weight as scikit-learn. You can reinstall abess via github to enjoy this new feature. We going to support this feature in the next pypi&conda version.

lindnemi commented 2 years ago

Thank you :) That was really quick!