[ENH]: Data Imputation
Open
Nobody has claimed this yet.
documentation
enhancement
- Dominant language
- Python
- Stars
- 33
- Forks
- 19
- PR merge metrics
- No merged PRs in 30d
Description
Which feature do you want to include?
How about also including data imputation inside run_cross_validation pipeline?
How do you imagine this integrated in julearn?
When use run_cross_validation, user can also add data_imputation steps like zscore.
Do you have a sample code that implements this outside of julearn?
No response
Anything else to say?
No response
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 locating the run_cross_validation entry point and reviewing how pipeline steps such as zscore are currently handled. Clarify which imputation methods and configuration are required, then identify the relevant tests; done should include documented imputation support in cross-validation with coverage for the supported behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100