SVMMaj: Implementation of the SVM-Maj Algorithm

Implements the SVM-Maj algorithm to train data with support vector machine as described in Groenen et al. (2008) <doi:10.1007/s11634-008-0020-9>. This algorithm uses two efficient updates, one for linear kernel and one for the nonlinear kernel.

Depends: R (≥ 2.13.0), stats, graphics
Imports: reshape2, scales, gridExtra, dplyr, ggplot2, kernlab
Suggests: utils, testthat, magrittr, xtable
Published: 2022-05-23
Author: Hoksan Yip, Patrick J.F. Groenen, Georgi Nalbantov
Maintainer: Hok San Yip <hoksan at>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: SVMMaj results


Reference manual: SVMMaj.pdf
Vignettes: paper


Package source: SVMMaj_0.2.9.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SVMMaj_0.2.9.1.tgz, r-oldrel (arm64): SVMMaj_0.2.9.1.tgz, r-release (x86_64): SVMMaj_0.2.9.1.tgz, r-oldrel (x86_64): SVMMaj_0.2.9.1.tgz
Old sources: SVMMaj archive


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