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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-release (arm64): SVMMaj_0.2.9.3.tgz, r-oldrel (arm64): 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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.