Add an over-parametrized dummy coding scheme
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statsmodels-request
well-defined-task-definitely-do-this
- Dominant language
- Python
- Stars
- 990
- Forks
- 106
- Avg merge
- 7d 34m
- Merged PRs (30d)
- 1
Description
To provide one way for users who definitely want overparametrized dummy coding to just do
C(myfactor, DummyDammit)
or whatever.
[Request from Josef, talked over at PyCon]
Contributor guide
No contributing guide indexed for this repository
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 how C(myfactor, ...) and the existing categorical coding schemes are implemented. Determine the intended API and behavior for an explicitly selectable over-parametrized dummy scheme, then add coverage showing that C(myfactor, DummyDammit) produces the expected coding.
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
- Mostly clear
- Newbie friendliness
- 25/100