mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines

R Submitted 03 December 2020 • Published 14 May 2021
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Editor: @arfon (all papers)
Reviewers: @JonnyTran (all reviews), @FedericoComoglio (all reviews)

Authors

Begüm D. Topçuoğlu (0000-0003-3140-537X), Zena Lapp (0000-0003-4674-2176), Kelly L. Sovacool (0000-0003-3283-829X), Evan Snitkin (0000-0001-8409-278X), Jenna Wiens (0000-0002-1057-7722), Patrick D. Schloss (0000-0002-6935-4275)

Citation

Topçuoğlu et al., (2021). mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines. Journal of Open Source Software, 6(61), 3073, https://doi.org/10.21105/joss.03073

@article{Topçuoğlu2021, doi = {10.21105/joss.03073}, url = {https://doi.org/10.21105/joss.03073}, year = {2021}, publisher = {The Open Journal}, volume = {6}, number = {61}, pages = {3073}, author = {Begüm D. Topçuoğlu and Zena Lapp and Kelly L. Sovacool and Evan Snitkin and Jenna Wiens and Patrick D. Schloss}, title = {mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines}, journal = {Journal of Open Source Software} }
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machine learning regression classification decision trees random forest xgboost support vector machines microbiology

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

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ISSN 2475-9066