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

Add set_internal_tuning() helper method for configuring internal hyperparameter optimization #1088

Open
sebffischer opened this issue Aug 17, 2024 · 0 comments

Comments

@sebffischer
Copy link
Member

Configuring the internal tuning of a Learner that supports it is somewhat tricky because one has to read through the lengthy parameter documentation. We (marc, bernd, me) decided to add a S3 generic set_internal_tuning(learner, ...) which makes this easier.

For xgboost, e.g. this would look something like:

set_internal_tuning.LearnerXgboost = function(learner, validate, early_stopping_rounds, nrounds, eval_metric) {
  # 1. set those parameters that were specified by the user in the learner
  # 2. afterwards check that early stopping is now properly enabled.
}
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

1 participant