rrecsys: Environment for Assessing Recommender Systems

Provides implementations of several popular recommendation systems. They can process standard recommendation datasets (user/item matrix) as input and generate rating predictions and recommendation lists. Standard algorithm implementations included in this package are: Global/Item/User-Average baselines, Item-Based KNN, FunkSVD, BPR and weighted ALS. They can be assessed according to the standard offline evaluation methodology for recommender systems using measures such as MAE, RMSE, Precision, Recall, AUC, NDCG, RankScore and coverage measures. The package is intended for rapid prototyping of recommendation algorithms and education purposes.

Depends: R (≥ 3.1.2), registry, proxy, MASS, stats, knitr
Imports: methods
Suggests: covr
Published: 2016-06-27
Author: Ludovik Çoba [aut, cre, cph], Markus Zanker [ctb]
Maintainer: Ludovik Çoba <lcoba at unishk.edu.al>
BugReports: https://github.com/ludovikcoba/rrecsys/issues
License: GPL-3
URL: https://github.com/ludovikcoba/rrecsys
NeedsCompilation: no
CRAN checks: rrecsys results


Reference manual: rrecsys.pdf
Vignettes: 0. Introduction and Installing rrecsys
1. A data set in rrecsys
2. Dispacher and registry
3. Non-personalized recommendations
4. Item-based k-nearest neighbors
5. Iterative updates for FunkSVD, BPR & wALS
6. Simon Funk's SVD
7. Bayesian Personalized Ranking
7. Weighted Alternated Least Squares
9. Predicting & recommending
10. Evaluation
11. Extendind rrecsys
Package source: rrecsys_0.9.5.4.tar.gz
Windows binaries: r-devel: rrecsys_0.9.5.4.zip, r-release: rrecsys_0.9.5.4.zip, r-oldrel: rrecsys_0.9.5.4.zip
OS X Mavericks binaries: r-release: rrecsys_0.9.5.4.tgz, r-oldrel: rrecsys_0.9.5.4.tgz
Old sources: rrecsys archive


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