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!
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.
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 I reckon the ecosystem is developing quite steadily and some blogposts I used seem to be a bit outdated.
This topic was automatically closed 7 days after the last reply. New replies are no longer allowed.
If you have a query related to it or one of the replies, start a new topic and refer back with a link.