Parameter processing for RLSSM models
Open
- Dominant language
- Python
- Stars
- 124
- Forks
- 24
- Avg merge
- 19h 32m
- Merged PRs (30d)
- 60
Description
**Current Implementation**
- I don't think there is a need to change the `from_user_specs()` function.
- But p_outlier handling might need a light wrapper around the likelihood function.
Contributor guide
Research direction
Start by tracing parameter processing for RLSSM models and reviewing from_user_specs(), then inspect the likelihood function where p_outlier is handled. The issue suggests a light wrapper may be needed, but it does not name files, tests, or a concrete completion criterion; clarify the intended behavior before making changes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100