L1 regularization in discriminant analysis

[ttrodrigz]

I am just getting acquainted with the discrim package and with discriminant analysis in general (discriminant analysis and its varieties are a little new to me).

I suppose my question is fairly straight forward: are there any computational engines (and corresponding tuning parameters) supported by the discrim package that will shrink model coefficients down to zero?

I see here that using the mda engine will allow for ridge/weight decay regularization. Is there anything available that would be more akin to L1 regularization? I am well-acquainted with lasso regression using multinom_reg() and logistic_reg() + glmnet, but I was wondering if something similar was available for discriminant analysis in the tidymodels framework.

Thanks!

[Max]

We haven't added any L1 methods to the package but can. sparseLDAcan be added.

[ttrodrigz]

Nice. Do you see this being on the short list of things to do for the package? I can add this as a feature request on GitHub.

Btw thanks for all the work the tidymodels team has put into this whole ecosystem, really enjoying it.

[Max]

A feature request on GitHub would be great. We often rotate between packages so it might be a month or so before I get to it.