Package: rrecsys
Type: Package
Title: Environment for Evaluating Recommender Systems
Version: 0.9.7.2
Date: 2018-02-10
Authors@R: c(person("Ludovik","Çoba", role=c("aut","cre","cph"), email="Ludovik.Coba@inf.unibz.it"), 
             person("Markus","Zanker", role="ctb",email="Markuz.Zanker@unibz.it"),
             person("Panagiotis","Symeonidis", role="ctb",email="Panagiotis.Symeonidis@unibz.it"))
URL: https://rrecsys.inf.unibz.it/
BugReports: https://github.com/ludovikcoba/rrecsys/issues
Description: 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)
        <doi:10.1007/978-0-387-85820-3_8>) for recommender systems
        using measures such as MAE, RMSE, Precision, Recall, F1, AUC,
        NDCG, RankScore and coverage measures. The package (Coba, et
        al.(2017) <doi: 10.1007/978-3-319-60042-0_36>) is intended for
        rapid prototyping of recommendation algorithms and education
        purposes.
Imports: methods, Rcpp
Depends: R (>= 3.1.2), registry, MASS, stats, knitr, ggplot2
License: GPL-3
VignetteBuilder: knitr
Encoding: UTF-8
LinkingTo: Rcpp
Repository: https://ludovikcoba.r-universe.dev
Date/Publication: 2022-05-15 09:45:21 UTC
RemoteUrl: https://github.com/ludovikcoba/rrecsys
RemoteRef: HEAD
RemoteSha: 8511f2770c10b30cabb630621c121b44afe4f5bd
NeedsCompilation: yes
Packaged: 2026-06-09 10:19:53 UTC; root
Author: Ludovik Çoba [aut, cre, cph],
  Markus Zanker [ctb],
  Panagiotis Symeonidis [ctb]
Maintainer: Ludovik Çoba <Ludovik.Coba@inf.unibz.it>