Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Mention other, preferred, packages in docs #615

Open
FBruzzesi opened this issue Feb 4, 2024 · 3 comments
Open

Mention other, preferred, packages in docs #615

FBruzzesi opened this issue Feb 4, 2024 · 3 comments
Labels
documentation We might describe something better good first issue Good for newcomers

Comments

@FBruzzesi
Copy link
Collaborator

QuantileRegressor made it into scikit-learn some time ago already.

As in the future other features could lose the experimental status and be incorporated as well (I am looking at you TunedThresholdClassifier) should we plan to deprecate them in future versions of scikit-lego?

@FBruzzesi FBruzzesi added the bug Something isn't working label Feb 4, 2024
@koaning
Copy link
Owner

koaning commented Feb 4, 2024

I've been wondering about this myself as well. The sklearn spline transformer now also does the repeating basis function trick ... so technically we won't need to have it around here.

Then again ... I also don't mind to brag. I think it was hosted on the lego side first, so maybe a message that just says "we're keeping it around for historical reasons because sklearn has support for it now" is fine? I don't mind to communicate that sklego is a testing ground for experimental ideas.

@FBruzzesi
Copy link
Collaborator Author

It seems fair and square! I will add a couple of info notes in the docstrings just to let users know.

@koaning koaning changed the title Deprecate QuantileRegression for scikit-learn QuantileRegressor Mention other, preferred, packages in docs Feb 5, 2024
@koaning
Copy link
Owner

koaning commented Feb 5, 2024

I'll write a list of items that might fall under this category, feel free to add.

  • Some of our fairness docs should point to fairlearn
  • The quantile docs should point to sklearn
  • The repeating basis trick should point to the spline transformer in sklearn.

@FBruzzesi FBruzzesi added documentation We might describe something better and removed bug Something isn't working labels Feb 5, 2024
@koaning koaning added the good first issue Good for newcomers label Mar 23, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
documentation We might describe something better good first issue Good for newcomers
Projects
None yet
Development

No branches or pull requests

2 participants