Shrinkage
rust
python
Regularized regression in Rust, with composable losses, penalties, and solvers, dense and sparse matrices.
Shrinkage is a Rust library for fitting regression models with penalties that shrink coefficients, select features, or encourage structure. It supports linear, logistic, and multivariate regression, with lasso, ridge, elastic net, SLOPE, Group LASSO, and fusion penalties.
The library combines losses, penalties, and solvers through a typed API. It supports dense and sparse matrices through LazyMatrix and fits regularization paths by reusing previous solutions. Python and R bindings are under development.
Citation
BibTeX citation:
@software{larsson2026,
author = {Larsson, Johan},
publisher = {Zenodo},
title = {Shrinkage},
date = {2026},
url = {https://doi.org/10.5281/zenodo.23613100},
doi = {10.5281/zenodo.23613100},
langid = {en}
}
For attribution, please cite this work as:
Larsson, Johan. 2026. Shrinkage. Zenodo, released. https://doi.org/10.5281/zenodo.23613100.