I am not sure if you have seen the recent release of the "pre-trained LASSO" which is now available in the package ptLasso. Not sure if it will find a home here in the tidymodels ecosystem, but I just wanted to bring it to your attention and open some discussion about its potential implementation.
The sales-pitch (from them):
Can pretraining help the lasso? Yes!
Here we present a framework for the lasso in which an overall model is fit to a large set of data, and then fine-tuned to a specific task. This latter dataset can be a subset of the original dataset, but does not need to be. Pretraining the lasso has a wide variety of applications, including stratified models, multinomial targets, multi-response models, conditional average treatment estimation and even gradient boosting.
This potential model engine may suffer from the same issues as the sparse group LASSO which may preclude its inclusion in tidymodels, which we previously discussed here FWIW: https://github.com/tidymodels/parsnip/issues/595
Hi
tidymodelsteam,I am not sure if you have seen the recent release of the "pre-trained LASSO" which is now available in the package
ptLasso. Not sure if it will find a home here in thetidymodelsecosystem, but I just wanted to bring it to your attention and open some discussion about its potential implementation.The sales-pitch (from them):
Paper: http://arxiv.org/pdf/2401.12911 Website: https://erincr.github.io/ptLasso/ R package: https://erincr.github.io/ptLasso/ Other helpful docs: https://www.erincraig.me/lasso-pretraining
This potential model engine may suffer from the same issues as the sparse group LASSO which may preclude its inclusion in
tidymodels, which we previously discussed here FWIW: https://github.com/tidymodels/parsnip/issues/595