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Add Lasso regularization to PoissonRegressor #22289
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Hey @ebatty, I would like to contribute to this issue. It would be my first contribution. Can you assign this to me? |
@Vandinimodi1595 This is likely not a good first issue. One needs to be familiar with scikit-learn's workflow and requirements for adding a new feature, which involves updates to the user guide, tests, examples & implementation. To learn about scikit-learn's workflow, a good first issue is #21350 @lorentzenchr As for inclusion, what do you think about adding other types of regularization into the GLMs? |
@thomasjpfan, Could you assign that issue #21350 for me then? |
That issue can not be assigned to a single person because it is a list of 229 items around the same issue. There has already been around ~ 30 people that worked on the issue. As of this writing, there is still a 170 items to go. You can read the issue to see how to begin working on it. |
Thank you @thomasjpfan, I will look into it. |
This is a duplicate of #16637 and definitely on my longer roadmap. #21808 is an important step in that direction as it will enable to compute Hessians for linear models, which will enable 2nd order coordinates descent, like glmnet. |
Looking at this now, I don't see the ability currently to use lasso or elastic net as valid regularization schemes in the PoissonRegressor class. Should this issue be reopened, since it hasn't been resolved? @lorentzenchr |
Describe the workflow you want to enable
Linear and logistic regression allow l1, l2, or elasticnet regularization. However, the Poisson regression class (which is amazing to have!) only allows L2 regularization.
Describe your proposed solution
Enable flexible regularization choices for the Generalized Linear Models
Describe alternatives you've considered, if relevant
No response
Additional context
No response
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