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: | 0.2.9.3 |
Depends: | R (≥ 2.13.0), stats, graphics, parallel |
Imports: | reshape2, scales, gridExtra, dplyr, ggplot2, kernlab |
Suggests: | utils, testthat, magrittr, xtable |
Published: | 2024-11-22 |
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 |
Reference manual: | SVMMaj.pdf |
Vignettes: |
paper (source, R code) |
Package source: | SVMMaj_0.2.9.3.tar.gz |
Windows binaries: | r-devel: SVMMaj_0.2.9.3.zip, r-release: SVMMaj_0.2.9.3.zip, r-oldrel: SVMMaj_0.2.9.3.zip |
macOS binaries: | r-devel (arm64): SVMMaj_0.2.9.3.tgz, r-release (arm64): SVMMaj_0.2.9.3.tgz, r-oldrel (arm64): SVMMaj_0.2.9.3.tgz, r-devel (x86_64): SVMMaj_0.2.9.3.tgz, r-release (x86_64): SVMMaj_0.2.9.3.tgz, r-oldrel (x86_64): SVMMaj_0.2.9.3.tgz |
Old sources: | SVMMaj archive |
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