SciML / SciML/DataDrivenDiffEq.jl
Document symbolic regression separately from SINDY?
Open
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 430
- Forks
- 58
- Avg merge
- 6h 29m
- Merged PRs (30d)
- 28
Description
Symbolic regressions are generally useful, and I think a few people have gotten confused when it's fully lumped in with SINDy. I think it could be good to have a page and tutorial specifically on symbolic regression, then do SINDy shortly afterwards.
Contributor guide
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 reviewing the existing SINDy documentation and tutorial structure in the repository. Create a separate symbolic regression page and tutorial, followed by the SINDy material, so the two topics are clearly distinguished; done means both workflows have their own documentation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100