rrecsys: Environment for Evaluating Recommender Systems

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.

Getting started

Package details

AuthorLudovik Çoba [aut, cre, cph], Markus Zanker [ctb], Panagiotis Symeonidis [ctb]
Date of publication2018-02-10 14:44:54 UTC
MaintainerLudovik Çoba <[email protected]>
URL https://rrecsys.inf.unibz.it/
Package repositoryView on CRAN
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rrecsys documentation built on Feb. 11, 2018, 3:13 p.m.