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.
| Version: | 0.2.9 |
| Depends: | R (≥ 2.13.0), stats, graphics |
| Imports: | reshape2, scales, gridExtra, dplyr, ggplot2, kernlab |
| Suggests: | utils, testthat, magrittr, xtable |
| Published: | 2019-01-26 |
| Author: | Hoksan Yip, Patrick J.F. Groenen, Georgi Nalbantov |
| Maintainer: | Hok San Yip <hoksan at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | SVMMaj results |
| Reference manual: | SVMMaj.pdf |
| Vignettes: |
paper |
| Package source: | SVMMaj_0.2.9.tar.gz |
| Windows binaries: | r-devel: SVMMaj_0.2.9.zip, r-release: SVMMaj_0.2.9.zip, r-oldrel: SVMMaj_0.2.9.zip |
| macOS binaries: | r-release: SVMMaj_0.2.9.tgz, r-oldrel: SVMMaj_0.2.9.tgz |
| Old sources: | SVMMaj archive |
Please use the canonical form https://CRAN.R-project.org/package=SVMMaj to link to this page.