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A toolkit for easily building and evaluating machine learning models.
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README.md

easyml

Project Status: Active - The project has reached a stable, usable state and is being actively developed.DOIBuild Status

A toolkit for easily building and evaluating machine learning models.

Installation

See installation instructions for the Python or R packages.

If you encounter a clear bug, please file a minimal reproducible example on github.

Citation

A whitepaper for easyml is available at https://doi.org/10.1101/137240. If you find this code useful please cite us in your work:

@article {Hendricks137240,
	author = {Hendricks, Paul and Ahn, Woo-Young},
	title = {Easyml: Easily Build And Evaluate Machine Learning Models},
	year = {2017},
	doi = {10.1101/137240},
	publisher = {Cold Spring Harbor Labs Journals},
	URL = {http://biorxiv.org/content/early/2017/05/12/137240},
	journal = {bioRxiv}
}

References

Hendricks, P., & Ahn, W.-Y. (2017). Easyml: Easily Build And Evaluate Machine Learning Models. bioRxiv, 137240. http://doi.org/10.1101/137240

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