recommenderlab: Lab for Developing and Testing Recommender Algorithms
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: |
1.0.6 |
Depends: |
R (≥ 3.5.0), Matrix, arules, proxy (≥ 0.4-26) |
Imports: |
registry, methods, utils, stats, irlba, recosystem, matrixStats |
Suggests: |
testthat |
Published: |
2023-09-20 |
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 |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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