Package: L0Learn
Type: Package
Title: Fast Algorithms for Best Subset Selection
Version: 2.0.3
Date: 2021-03-28
Authors@R: c(
    person("Hussein", "Hazimeh", email = "hazimeh@mit.edu", role = c("aut", "cre")),
    person("Rahul", "Mazumder", email = "rahulmaz@mit.edu", role = "aut"),
    person("Tim", "Nonet", email = "tim.nonet@gmail.com", role = "aut"))
Description: 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);
    the link is provided in the URL field below.
URL: https://pubsonline.informs.org/doi/10.1287/opre.2019.1919
        https://github.com/hazimehh
BugReports: https://github.com/hazimehh/L0Learn/issues
License: MIT + file LICENSE
Depends: R (>= 3.3.0)
SystemRequirements: C++11
Imports: Rcpp (>= 0.12.13), Matrix, methods, ggplot2, reshape2, MASS
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat, pracma, raster
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-03-28 21:38:21 UTC; hh
Author: Hussein Hazimeh [aut, cre],
  Rahul Mazumder [aut],
  Tim Nonet [aut]
Maintainer: Hussein Hazimeh <hazimeh@mit.edu>
Repository: CRAN
Date/Publication: 2021-04-03 13:50:28 UTC
Built: R 4.0.2; x86_64-apple-darwin17.0; 2021-04-04 11:03:04 UTC; unix
Archs: L0Learn.so.dSYM
