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>.
copied from cf-post-staging / r-recommenderlab| Label | Latest Version |
|---|---|
| main | 1.0.7 |
