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>.
Package details |
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Maintainer | |
License | GPL-2 |
Version | 1.0.6 |
URL | https://github.com/mhahsler/recommenderlab |
Package repository | View on GitHub |
Installation |
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