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].
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. arXiv:1809.03125 [cs.IR].
Throughout this documentation, we use the notation of .
- Loading Data
- Splitting Data
- Batch-Running Recommenders
- Evaluating Recommender Output
- Documenting Experiments
Indices and tables
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.