menelaus 0.2.0

This library implements algorithms for detecting data drift and concept drift for ML and statistics applications.

Menelaus implements algorithms for the purposes of drift detection. Drift detection is a branch of machine learning focused on the detection of unforeseen shifts in data. The relationships between variables in a dataset are rarely static and can be affected by changes in both internal and external factors, e.g. changes in data collection techniques, external protocols, and/or population demographics. Both undetected changes in data and undetected model underperformance pose risks to the users thereof. The aim of this package is to enable monitoring of data and machine learning model performance.

For full documentation, see:

• GitHub: https://github.com/mitre/menelaus

• ReadTheDocs: https://menelaus.readthedocs.io/en/latest/