How to construct a polynomial for numerical data?
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 990
- Forks
- 106
- Avg merge
- 7d 34m
- Merged PRs (30d)
- 1
Description
For example I have some variables "x1, x2, x3, ...", and want all polynomials with a simple choice on the degree. The only solution I know so far is by using preprocessing.PolynomialFeatures in sklearn. But I can't see why it cannot be done simply in patsy.
Thanks.
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 reviewing the issue's referenced scikit-learn entry point, preprocessing.PolynomialFeatures, and compare it with Patsy's formula interface. The issue does not name Patsy files or tests; the work would need a decided approach for constructing polynomials and a documented or implemented way to verify that behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, scikit-learn
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100