slimrec: Sparse Linear Method to Predict Ratings and Top-N Recommendations

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
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

Downloads:

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
OS X El Capitan binaries: r-release: slimrec_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: not available

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