accSDA: Accelerated Sparse Discriminant Analysis

Implementation of sparse linear discriminant analysis, which is a supervised classification method for multiple classes. Various novel optimization approaches to this problem are implemented including alternating direction method of multipliers ('ADMM'), proximal gradient (PG) and accelerated proximal gradient ('APG') (See Atkins 'et al'. <doi:10.48550/arXiv.1705.07194>). Functions for performing cross validation are also supplied along with basic prediction and plotting functions. Sparse zero variance discriminant analysis ('SZVD') is also included in the package (See Ames and Hong, <doi:10.48550/arXiv.1401.5492>). See the 'github' wiki for a more extended description.

Version: 1.1.3
Depends: R (≥ 3.2)
Imports: MASS (≥ 7.3.45), ggplot2 (≥ 2.1.0), grid (≥ 3.2.2), gridExtra (≥ 2.2.1)
Published: 2024-03-06
DOI: 10.32614/CRAN.package.accSDA
Author: Gudmundur Einarsson [aut, cre, trl], Line Clemmensen [aut, ths], Brendan Ames [aut], Summer Atkins [aut]
Maintainer: Gudmundur Einarsson <gumeo140688 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: accSDA citation info
Materials: README NEWS
CRAN checks: accSDA results


Reference manual: accSDA.pdf


Package source: accSDA_1.1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): accSDA_1.1.3.tgz, r-oldrel (arm64): accSDA_1.1.3.tgz, r-release (x86_64): accSDA_1.1.3.tgz, r-oldrel (x86_64): accSDA_1.1.3.tgz
Old sources: accSDA archive


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