By sampling your data, running the Support-Vector-Machine algorithm on these samples in parallel on your own machine and letting your models vote on a prediction, we return much faster predictions than the regular Support-Vector-Machine and possibly even more accurate predictions.
| Version: | 0.1-9 |
| Depends: | R (≥ 2.14.0), e1071 (≥ 1.6-3) |
| Imports: | parallel (≥ 3.1.1), foreach (≥ 1.2.0), doParallel (≥ 1.0.8) |
| Published: | 2015-06-26 |
| Author: | Wannes Rosiers (InfoFarm) |
| Maintainer: | Wannes Rosiers <wannes.rosiers at infofarm.be> |
| License: | GPL-2 |
| URL: | www.infofarm.be |
| NeedsCompilation: | no |
| CRAN checks: | parallelSVM results |
| Reference manual: | parallelSVM.pdf |
| Package source: | parallelSVM_0.1-9.tar.gz |
| Windows binaries: | r-devel: parallelSVM_0.1-9.zip, r-release: parallelSVM_0.1-9.zip, r-oldrel: parallelSVM_0.1-9.zip |
| macOS binaries: | r-release: parallelSVM_0.1-9.tgz, r-oldrel: parallelSVM_0.1-9.tgz |
| Old sources: | parallelSVM archive |
Please use the canonical form https://CRAN.R-project.org/package=parallelSVM to link to this page.