Fast Algorithms for Best Subset Selection R package L0Learn version 2.1.0 Highly optimized toolkit for approximately solving L0-regularized learning problems (a.k.a. best subset selection). The algorithms are based on coordinate descent and local combinatorial search. For more details, check the paper by Hazimeh and Mazumder (2020) <doi:10.1287/opre.2019.1919>. Software Depends: R (>= 3.3.0) Imports: Rcpp (>= 0.12.13), Matrix, methods, ggplot2, reshape2, MASS LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, testthat, pracma, raster, covr Hussein Hazimeh <husseinhaz@gmail.com> Comprehensive R Archive Network (CRAN) Hussein Hazimeh [aut, cre], Rahul Mazumder [aut], Tim Nonet [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=L0Learn/LICENSE) 2023-03-07 application/tgz https://CRAN.R-project.org/package=L0Learn doi:10.32614/CRAN.package.L0Learn