Parameter tuning: future plans
Open
Nobody has claimed this yet.
enhancement
- Dominant language
- Python
- Stars
- 12
- Forks
- 11
- Avg merge
- 7d 23h
- Merged PRs (30d)
- 3
Description
Right now, for parameter tuning (#16 ) we have a limited set of options. Ideally we would use something like MLOS to tune them more formally. This will take a bit of work, but would be super cool.
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 reading issue #16 on parameter tuning and the linked MLOS project to understand the current options and possible formal tuning approach. The issue names no files or tests; define the desired tuning scope, integration boundaries, and completion criteria before implementation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100