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) <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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.9.7.3.1 |
rolling linux/jammy R-4.5 | rrecsys_0.9.7.3.1.tar.gz |
1.0 MiB |
0.9.7.3.1 |
rolling linux/noble R-4.5 | rrecsys_0.9.7.3.1.tar.gz |
1.0 MiB |
0.9.7.3.1 |
rolling source/ R- | rrecsys_0.9.7.3.1.tar.gz |
672.2 KiB |
0.9.7.3.1 |
latest linux/jammy R-4.5 | rrecsys_0.9.7.3.1.tar.gz |
1.0 MiB |
0.9.7.3.1 |
latest linux/noble R-4.5 | rrecsys_0.9.7.3.1.tar.gz |
1.0 MiB |
0.9.7.3.1 |
latest source/ R- | rrecsys_0.9.7.3.1.tar.gz |
672.2 KiB |
0.9.7.3.1 |
2026-04-26 source/ R- | rrecsys_0.9.7.3.1.tar.gz |
672.2 KiB |
0.9.7.3.1 |
2026-04-23 source/ R- | rrecsys_0.9.7.3.1.tar.gz |
672.2 KiB |
0.9.7.3.1 |
2026-04-09 windows/windows R-4.5 | rrecsys_0.9.7.3.1.zip |
1.4 MiB |
0.9.7.3.1 |
2025-04-20 source/ R- | rrecsys_0.9.7.3.1.tar.gz |
672.2 KiB |