By sampling your data, running the provided classifier 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 machine learning algorithm and possibly even more accurate predictions.
Version: | 1.2 |
Depends: | R (≥ 2.14.0) |
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: | parallelML results |
Reference manual: | parallelML.pdf |
Package source: | parallelML_1.2.tar.gz |
Windows binaries: | r-devel: parallelML_1.2.zip, r-release: parallelML_1.2.zip, r-oldrel: parallelML_1.2.zip |
macOS binaries: | r-release: parallelML_1.2.tgz, r-oldrel: parallelML_1.2.tgz |
Old sources: | parallelML archive |
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