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L0Learn: A Scalable Package for Sparse Learning using L0 Regularization
- Publication Year :
- 2022
-
Abstract
- We present L0Learn: an open-source package for sparse linear regression and classification using $\ell_0$ regularization. L0Learn implements scalable, approximate algorithms, based on coordinate descent and local combinatorial optimization. The package is built using C++ and has user-friendly R and Python interfaces. L0Learn can address problems with millions of features, achieving competitive run times and statistical performance with state-of-the-art sparse learning packages. L0Learn is available on both CRAN and GitHub (https://cran.r-project.org/package=L0Learn and https://github.com/hazimehh/L0Learn).<br />Comment: Accepted to JMLR (MLOSS)
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2202.04820
- Document Type :
- Working Paper