ModelOriented / ModelOriented/DALEX
Bayesian regularization support in DALEX
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question ❔
- Dominant language
- Python
- Stars
- 1.5k
- Forks
- 172
- PR merge metrics
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Description
In some social science fields large data do not exist and researchers must make decisions using small number of samples (p >> n problem)
Good to see support in R (tfprobability, brnn packages)
Wondering if the DALEX team has any thoughts/comments on this?
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
No file, test, or entry point is identified. First clarify whether Bayesian regularization is expected in DALEX itself or only discussion of existing R packages, then define the supported scope and acceptance criteria before locating the relevant modeling and explanation paths.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, r
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100