The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Sparse Linear Method(SLIM) predicts ratings and top-n recommendations suited for sparse implicit positive feedback systems. SLIM is decomposed into multiple elasticnet optimization problems which are solved in parallel over multiple cores. The package is based on "SLIM: Sparse Linear Methods for Top-N Recommender Systems" by Xia Ning and George Karypis <doi:10.1109/ICDM.2011.134>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.3.3), stats (≥ 3.3.3) |
| Imports: | assertthat (≥ 0.1), parallel (≥ 3.3.3), Matrix (≥ 1.2.8), glmnet (≥ 2.0.5), bigmemory (≥ 4.5.19), pbapply (≥ 1.3.2) |
| Published: | 2017-03-25 |
| DOI: | 10.32614/CRAN.package.slimrec |
| Author: | Srikanth KS [aut, cre] |
| Maintainer: | Srikanth KS <sri.teach at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | slimrec results |
| Reference manual: | slimrec.pdf |
| Package source: | slimrec_0.1.0.tar.gz |
| Windows binaries: | r-devel: slimrec_0.1.0.zip, r-release: slimrec_0.1.0.zip, r-oldrel: slimrec_0.1.0.zip |
| macOS binaries: | r-release (arm64): slimrec_0.1.0.tgz, r-oldrel (arm64): slimrec_0.1.0.tgz, r-release (x86_64): slimrec_0.1.0.tgz, r-oldrel (x86_64): slimrec_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=slimrec to link to this page.
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.
Health stats visible at Monitor.