Provides a research infrastructure to develop and evaluate
collaborative filtering recommender algorithms. This includes a sparse
representation for user-item matrices, many popular algorithms, top-N recommendations,
and cross-validation. Hahsler (2022) <doi:10.48550/arXiv.2205.12371>.
| Version: |
1.0.7 |
| Depends: |
R (≥ 4.5.0), Matrix, arules (≥ 1.7-11), proxy (≥ 0.4-26) |
| Imports: |
registry, methods, utils, stats, irlba, recosystem, matrixStats |
| Suggests: |
testthat |
| Published: |
2025-05-31 |
| DOI: |
10.32614/CRAN.package.recommenderlab |
| Author: |
Michael Hahsler 
[aut, cre, cph],
Bregt Vereet [ctb] |
| Maintainer: |
Michael Hahsler <mhahsler at lyle.smu.edu> |
| BugReports: |
https://github.com/mhahsler/recommenderlab/issues |
| License: |
GPL-2 |
| Copyright: |
(C) Michael Hahsler |
| URL: |
https://github.com/mhahsler/recommenderlab |
| NeedsCompilation: |
no |
| Classification/ACM: |
G.4, H.2.8 |
| Citation: |
recommenderlab citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
recommenderlab results |