JuliaAI / JuliaAI/MLJLinearModels.jl
Option to scale loss by `n`
Open
Nobody has claimed this yet.
API
enhancement
low priority
- Dominant language
- Julia
- Stars
- 86
- Forks
- 15
- PR merge metrics
- No merged PRs in 30d
Description
In case users prefer this;
that means though that things should be ScaledLosss{...} in fit methods etc, it shouldn't change much otherwise.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the fit methods mentioned in the issue and tracing how losses are passed through them. Determine how an optional ScaledLosss form would affect loss scaling and define the expected behavior for existing methods. Done means users can opt into scaling by n without other behavioral changes; the issue names no tests or files to run.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100