SVMMaj: Implementation of the SVM-Maj Algorithm

Implements the SVM-Maj algorithm to train data with support vector machine <doi:10.1007/s11634-008-0020-9>. This algorithm uses two efficient updates, one for linear kernel and one for the nonlinear kernel.

Version: 0.2.9.2
Depends: R (≥ 2.13.0), stats, graphics
Imports: reshape2, scales, gridExtra, dplyr, ggplot2, kernlab
Suggests: utils, testthat, magrittr, xtable
Published: 2024-08-19
DOI: 10.32614/CRAN.package.SVMMaj
Author: Hoksan Yip [aut, cre], Patrick J.F. Groenen [aut], Georgi Nalbantov [aut]
Maintainer: Hoksan Yip <hoksan at gmail.com>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: SVMMaj results

Documentation:

Reference manual: SVMMaj.pdf
Vignettes: paper (source, R code)

Downloads:

Package source: SVMMaj_0.2.9.2.tar.gz
Windows binaries: r-devel: SVMMaj_0.2.9.2.zip, r-release: SVMMaj_0.2.9.2.zip, r-oldrel: SVMMaj_0.2.9.2.zip
macOS binaries: r-release (arm64): SVMMaj_0.2.9.2.tgz, r-oldrel (arm64): SVMMaj_0.2.9.2.tgz, r-release (x86_64): SVMMaj_0.2.9.2.tgz, r-oldrel (x86_64): SVMMaj_0.2.9.2.tgz
Old sources: SVMMaj archive

Linking:

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