CRAN/E | L0Learn

L0Learn

Fast Algorithms for Best Subset Selection

Installation

About

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.

pubsonline.informs.org/doi/10.1287/opre.2019.1919 https://github.com/hazimehh
pubsonline.informs.org/doi/10.1287/opre.2019.1919 https://github.com/hazimehh
System requirements C++11
Bug report File report

Key Metrics

Version 2.0.3
R ≥ 3.3.0
Published 2021-04-03 1112 days ago
Needs compilation? yes
License MIT
License File
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Maintainer

Maintainer

Hussein Hazimeh

hazimeh@mit.edu

Authors

Hussein Hazimeh

aut / cre

Rahul Mazumder

aut

Tim Nonet

aut

Material

ChangeLog
Reference manual
Package source

Vignettes

L0Learn Vignette

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

L0Learn archive

Depends

R ≥ 3.3.0

Imports

Rcpp ≥ 0.12.13
Matrix
methods
ggplot2
reshape2
MASS

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LinkingTo

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