Skip to content
This repository has been archived by the owner on Mar 6, 2021. It is now read-only.

Adding more classifier implementations - XGBoost and support for more scoring functions (precision, recall, other custom metric etc.) #3

Open
shivam6294 opened this issue Nov 14, 2016 · 1 comment

Comments

@shivam6294
Copy link

Hey! Great work on simplifying the process of building ensembles. I was trying to use this, but I found that the GBM implementation of Scikit learn is far too slow for my needs. We could possibly include a faster implementation, aka XGBoost.

I would love to help out with this, will make a PR soon after adding XGBoost. Also keen on helping you add more scoring functions (precision, recall, matthew's coefficient, and support for custom scoring functions similar to the scikit learn api)

Cheers!

@joofeloof
Copy link

I'm pretty sure I have this working on the classifier side if you see my fork. It's not the cleanest but maybe it will be useful to you?
I never had time to clean things up and do a PR, but it doesn't seem like dclambert is actively working on this given the other open pulls?

Sign up for free to subscribe to this conversation on GitHub. Already have an account? Sign in.
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants