User defined cuts for tree-based methods
Nobody has claimed this yet.
- Dominant language
- R
- Stars
- 146
- Forks
- 23
- PR merge metrics
- No merged PRs in 30d
Description
Feature
It isn't currently clear how step_collapse_cart and other methods for numeric predictors determine how many groups to select. It could be useful to add a parameter cut_depth that would allow users to specify how far down the decision tree to make cuts to collapse/group values. Alternatively, a groups parameter that allows users to specify the number of groups they want to retain, which would return <= groups based on cutting the tree could also be a useful feature for users.
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 step_collapse_cart and the other numeric-predictor methods to understand how tree cuts currently determine groups. Clarify whether the API should expose cut_depth, groups, or both, then define and test the expected behavior for retaining at most the requested number of groups.
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
- 35/100