How to speed up XGboost modelling with tidymodels

[Enuma]

Hi.
I am looking for a way to speed up XGboost performance. Using Tidymodels route with parsnip::boost_tree in regression mode. I am still fresh when it comes to XGboost. After looking up the topic on the internet, the best bet seems to use histogram-based trees and potentially use gpu for computing.

Thanks!

[Max]

lightgbm is a lot faster. You can use that via tidymodels via the bonsai package.

You can pass histogram related options via set_engine().

Also, if you are using the tidymodels tuning functions, it is better to parallel process via tidymodels instead of the parallel processing available within each xgboost fit.

[Enuma]

Thanks Max! What is the most up to date tidymodels instructional? I reckon the ecosystem is developing quite steadily and some blogposts I used seem to be a bit outdated.

[Max]

tidymodels.org and tmwr.org