LensKit is a set of Python tools for experimenting with and studying recommender systems. It provides support for training, running, and evaluating recommender algorithms in a flexible fashion suitable for research and education.
LensKit for Python (also known as LKPY) is the successor to the Java-based LensKit toolkit and a part of the LensKit project.
If you use Lenskit in published research, cite [LKPY].
Throughout this documentation, we use the notation of :citeEkstrand2019-dh.
install GettingStarted examples Release Notes <https://github.com/lenskit/lkpy/releases>
datasets crossfold batch evaluation/index
interfaces algorithms basic ranking bias knn mf addons
performance diagnostics impl-tips
util internals
references
genindexmodindexsearch
This material is based upon work supported by the National Science Foundation under Grant No. IIS 17-51278. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
- LKPY
Michael D. Ekstrand. 2020. LensKit for Python: Next-Generation Software for Recommender Systems Experiments. In <cite>Proceedings of the 29th ACM International Conference on Information and Knowledge Management</cite> (CIKM '20). DOI:`10.1145/3340531.3412778 <https://dx.doi.org/10.1145/3340531.3412778>_. arXiv:`1809.03125 <https://arxiv.org/abs/1809.03125>_ [cs.IR].