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LensKit

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].

[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].

Resources

.. toctree::
   :maxdepth: 2
   :caption: Overview

   install
   GettingStarted
   examples
   Release Notes <https://github.com/lenskit/lkpy/releases>


.. toctree::
   :maxdepth: 2
   :caption: Running Experiments

   datasets
   crossfold
   batch
   evaluation/index


.. toctree::
    :maxdepth: 1
    :caption: Algorithms

    interfaces
    algorithms
    basic
    ranking
    bias
    knn
    mf
    tf
    hpf
    implicit


.. toctree::
    :maxdepth: 2
    :caption: Tips and Tricks

    performance
    diagnostics
    impl-tips


.. toctree::
    :maxdepth: 2
    :caption: Configuration and Internals

    util
    internals

Indices and tables

Acknowledgements

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.