Investigate whether we can expand the types of outcomes for likelihood encoding steps
Open
Nobody has claimed this yet.
feature
target encoding
- Dominant language
- R
- Stars
- 146
- Forks
- 23
- PR merge metrics
- No merged PRs in 30d
Description
Some only do numeric and binary classification, but could be expanded to multi-class classification and maybe even survival
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
Locate the package's likelihood encoding steps and review how they currently handle numeric and binary classification outcomes. Investigate the feasibility and scope of multi-class and survival outcomes, then document a clear recommendation and the behavior that would define completion.
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
- Needs clarification
- Newbie friendliness
- 25/100