scikit-learn / scikit-learn/scikit-learn
enable regression step coefs after fit
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- Python
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Description
For a lot of different analyses that come upon model training, in special for PLSRegression and the like, it is necessary to have the resulting coefficients of the regression step only, the "alpha" coefficients in the documentation 1.8.1.2. Predicting the targets Y
https://scikit-learn.org/stable/modules/cross_decomposition.html#cross-decomposition
I suggest including them in future releases of sklearn
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
Read the cross-decomposition documentation section on predicting targets Y and inspect PLSRegression and related models to understand the requested regression-step, or “alpha,” coefficients. The work is done when those coefficients are exposed in a future scikit-learn release with behavior matching the documented regression step.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100