Andy Dienes
Andy Dienes
I would also enjoy this feature
it is documented as public API here https://juliaai.github.io/MLJLinearModels.jl/stable/api/#MLJLinearModels.ElasticNetRegression and furthermore the `fit` and `predict` methods in `MLJLinearModels.jl` only work on `ElasticNetRegression`, not `ElasticNetRegressor`, and these methods are surely public API...
is projecting to R+ at each step what sklearn does here ? https://github.com/scikit-learn/scikit-learn/blob/286f0c9d17019e52f532d63b5ace9f8e1beb5fe5/sklearn/linear_model/_cd_fast.pyx#L568C5-L568C33 it looks like it but I'm not entirely sure. I guess they are doing coordinate descent rather...
> if the plan is to only use the dependency for CLasso then I'm not super highly in favour fair enough --- although if eventually going that route, I will...
`fit(::Type{T}, glr::GLR, X::AbstractMatrix{
ref https://github.com/JuliaLang/julia/issues/51729
I still do not understand the difference between this proposal and what `@assert` (is intended to be), except for reversing the opt-in / opt-out default
the regression still exists on 1.11, but it looks like it's resolved on master, so this would only appear specifically in the 1.11.x releases (unless it re-regresses)
this issue should probably get some labels (or just closed as not-planned if that is the case)
I think it would be a very bad choice to make the mean of `Date` to round to a `Date` like is proposed. To me it feels pretty hacky and...