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 project.
To install the current release with Anaconda (recommended):
conda install -c lenskit lenskit
Or you can use
pip install lenskit
To use the latest development version, install directly from GitHub:
pip install git+https://github.com/lenskit/lkpy
Then see Getting Started.
- Getting Started
- Algorithm Interfaces
- Crossfold preparation
- Batch-Running Recommenders
- Evaluating Recommender Output
- Data Set Utilities
- Random Number Generation
- Utility Functions
- Errors and Diagnostics
- Algorithm Implementation Tips
- LensKit Internals
- Release Notes
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.