A toolkit for easily building and evaluating machine learning models.
See installation instructions for the Python or R packages.
If you encounter a clear bug, please file a minimal reproducible example on github.
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}
}
Hendricks, P., & Ahn, W.-Y. (2017). Easyml: Easily Build And Evaluate Machine Learning Models. bioRxiv, 137240. http://doi.org/10.1101/137240
