Hi Parker,

We strongly urge new contributors to start with small issues
(documentation, small fixes, etc.) to gain confidence in the contribution
procedure, etc. Once you've worked on small issues and understand better
what comes through the issue tracker, you can consider bigger contributions.

We have indeed proposed support for imblearn-like Pipeline extensions (
https://github.com/scikit-learn/scikit-learn/issues/3855#issuecomment-357949997).
And yes, we're in need of a contributor there, but I would rather review
and merge smaller pieces of your work, before finding a large one that
needs a lot of changes before merge.

Joel

On Wed, 5 Dec 2018 at 12:15, parker x <szx9...@gmail.com> wrote:

> Dear scikit-learn developers,
>
> My name is Parker, and I'm a data scientist.
>
> Scikit-learn is a great ML library that I work frequently for work and
> personal projects. I have always wanted to contribute something to the
> scikit-learn community, and I am wondering if you could give some opinions
> on following two ideas for contribution.
>
> My first idea is to integrate another python library 'imbalanced-learn'
> into scikit-learn so that people could also use scikit-learn to deal with
> imbalance issues.
>
> Another idea is to combine those scikit-learn built-in feature selection
> functions into one automated feature selection function that might benefit
> those users who are not familiar with feature selection process.
>
> Looking forward to your suggestions! And thank you very much for your time!
>
> Best,
> Parker
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