Tuning of imputation hyperparameters
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- Dominant language
- R
- Stars
- 117
- Forks
- 36
- Avg merge
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- Merged PRs (30d)
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Description
Feature
In situations when I am imputing data as a recipe step, I would like to be able to tune the hyperparameters of the imputation method - which I anticipate is going to be a nightmare to implement, especially when parameters are passed between packages. For example, imputing with step_bagimpute uses ipred, which has its own hyperparameters but also passes on hyperparameters to rpart!
# the ipred hyperparameters, e.g. nbagg, can be set:
step_bagimpute(options = list(nbagg = 25))
# I'd like to be able to do something like:
step_bagimpute(options = list(nbagg = tune()))
But there's another level of HPs that ipred passes on to rpart, and it would be nice to be able to tune them as well.
# HPs can be passed through ipred to rpart
step_bagimpute(options = list(control = rpart::rpart.control(minsplit = 10))
# but it would be great to tune even these "next level" parameters:
step_bagimpute(options = list(control = rpart::rpart.control(minsplit = tune()))
Good luck!
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 with the step_bagimpute examples in the issue and inspect how dials represents tuneable parameters across the ipred and rpart::rpart.control entry points. Done would mean supporting tune() for ipred options such as nbagg and nested rpart parameters such as minsplit, with the resulting values available for tuning.
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
- 20/100