Smoothing of cross-validated predictive performance
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enhancement
- Dominant language
- R
- Stars
- 114
- Forks
- 31
- PR merge metrics
- No merged PRs in 30d
Description
As suggested by @avehtari, it would be good to support smoothing of cross-validated (submodel) predictive performance results in plot.vsel(). This smoothing should then also be integrated into the model size decision rule of suggest_size().
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 names plot.vsel() and suggest_size() as the entry points; locate their implementations and read the existing predictive-performance tests first. Done means smoothing is supported for cross-validated submodel performance in plot.vsel() and is also used by suggest_size() when deciding model size.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100