rrecsys (0.9.7.3)

Environment for Evaluating Recommender Systems.

https://rrecsys.inf.unibz.it/
http://cran.r-project.org/web/packages/rrecsys

Processes standard recommendation datasets (e.g., a user-item rating matrix) as input and generates rating predictions and lists of recommended items. Standard algorithm implementations which are included in this package are the following: Global/Item/User-Average baselines, Weighted Slope One, Item-Based KNN, User-Based KNN, FunkSVD, BPR and weighted ALS. They can be assessed according to the standard offline evaluation methodology (Shani, et al. (2011) ) for recommender systems using measures such as MAE, RMSE, Precision, Recall, F1, AUC, NDCG, RankScore and coverage measures. The package (Coba, et al.(2017) ) is intended for rapid prototyping of recommendation algorithms and education purposes.

Maintainer: Ludovik oba
Author(s): Ludovik oba [aut, cre, cph], Markus Zanker [ctb], Panagiotis Symeonidis [ctb]

License: GPL-3

Uses: ggplot2, knitr, MASS, Rcpp, registry

Released about 2 years ago.