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Tools to compare metrics between datasets, accounting for population differences and invariant features.
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Bump ipython from 7.5.0 to 8.10.0 
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README.md

Lumos

Lumos is a library to compare metrics between two datasets, accounting for population differences and invariant features. Lumos is described in this technical paper:

  @inproceedings{Pool2020,
	title="Lumos: A Library for Diagnosing Metric Regressions in Web-Scale Applications",
	author="Jamie Pool, Ebrahim Beyrami, Vishak Gopal, Ashkan Aazami, Jayant Gupchup, Jeff Rowland, Binlong Li, Pritesh Kanani, Ross Cutler, Johannes Gehrke",
	booktitle="Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
	year="2020"
}

Install

You can install latest release of Lumos directly from source:

pip install git+https://github.com/microsoft/MS-Lumos

Examples

Please refer to the examples folder.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.