rexmex (conda): **reXmeX** is a recommender system evaluation metric library.  Please look at the **[Documentation](https://rexmex.readthedocs.io/en/latest/)** and **[External Resources](https://rexmex.readthedocs.io/en/latest/notes/resources.html)**.  **reXmeX** consists of utilities for recommender system evaluation. First, it provides a comprehensive collection of metrics for the evaluation of recommender systems. Second, it includes a variety of methods for reporting and plotting the performance results. Implemented metrics cover a range of well-known metrics and newly proposed metrics from data mining ([ICDM](http://icdm2019.bigke.org/), [CIKM](http://www.cikm2019.net/), [KDD](https://www.kdd.org/kdd2020/)) conferences and prominent journals.  PyPI: [https://pypi.org/project/rexmex/](https://pypi.org/project/rexmex/)
Keywords: coverage|deep-learning|evaluation|machine-learning|metric|metrics|mrr|personalization|precision|rank|ranking|recall|recommender|recommender-system|recsys|rsquared