SciML / SciML/DataDrivenDiffEq.jl
Sparse regression methods in pure Julia
Open
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 430
- Forks
- 58
- Avg merge
- 6h 29m
- Merged PRs (30d)
- 28
Description
https://arxiv.org/abs/1902.06547 to discreminate between six different algorithms.
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
The issue links to arXiv:1902.06547 and asks for sparse regression methods in pure Julia to discriminate between six algorithms. Start by reading the paper and locating the relevant extension point in the repository; completion criteria, affected files, tests, and the six algorithms are not specified.
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
- 20/100