scikit-learn / scikit-learn/scikit-learn
Weights for sklearn.model_selection.KFold
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- Dominant language
- Python
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Description
Describe the workflow you want to enable
Kfold with weights. For example stratified kfold is with equal weights for all classes.
Describe your proposed solution
Please let me know if there is such feature already available. If not, I will describe in detail.
Describe alternatives you've considered, if relevant
Stratiied kfold can hve this as an argument
Additional context
I need this to unequally weigh the classes in imbalanced task and generate dataset for another stage of process
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 reading the sklearn.model_selection.KFold entry point and its documentation, then compare it with stratified k-fold behavior. Determine whether weighted classes or weighted fold assignment is already supported, and clarify the expected weighting semantics before proposing implementation work.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100