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reiinakano / xcessiv

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
http://xcessiv.readthedocs.io
Apache License 2.0
1.27k stars 105 forks source link

Add new preset estimators, metrics, and cv iterators #15

Open reiinakano opened 7 years ago

reiinakano commented 7 years ago

Sklearn has a TON of estimators, metrics, and cv iterators that could trivially be added to the xcessiv.presets package. I'm a bit focused on other issues to bother adding them all.

Anyone who can help add to the list can easily do so.

Adding preset estimators/metrics/cvs is very easy. There's literally no need to understand how the rest of Xcessiv works, just take a look and copy the patterns in the xcessiv.presets package. Also, add corresponding relevant tests for your addition.

Please keep PR's limited to one feature addition only for easy debugging and reformatting if needed. Of course, you can submit as many PR's as you like :)

techscientist commented 7 years ago

@reiinakano Hey, I just wanted to say that this is an AWESOME library! I'm currently a Kaggle novice, so this library is great! Also, I might be able to work on this later, so I'll send you a pull request once I've made some updates. Thanks!

reiinakano commented 7 years ago

@techscientist thank you for your kind feedback!

I would love PRs. Thank you!

enisnazif commented 7 years ago

Am also interested on working on this, I'll start soon :)

robertmartin8 commented 6 years ago

At some stage I would like to contribute with this, but as I am new, I would like to clarify what you mean by

add corresponding relevant tests for your addition

What would be the scope of such tests?

reiinakano commented 6 years ago

You can just copy the style of existing tests for each one that you add :) it's probably simpler than adding the preset code itself