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

Custom loss function #36

Open
ogencoglu opened this issue Dec 2, 2024 · 2 comments
Open

Custom loss function #36

ogencoglu opened this issue Dec 2, 2024 · 2 comments

Comments

@ogencoglu
Copy link

Ability to define arbitrary loss function just like in lightgbm would be great. Any such plans?

@deadsoul44
Copy link
Contributor

It is part of the plan, but this might take a while. If you need any specific loss function, let me know.

@ogencoglu
Copy link
Author

The ability to define different custom loss functions for different subsets of the training data would be my use case. I can do this with lightgbm (a bit hack-ish but gets the job done). My loss function is not constant as it is part of an optimization framework. Obviously gradients and Hessians should be available but there are frameworks for approximating those.

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

No branches or pull requests

2 participants