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mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines
An interface to build machine learning models for classification and regression problems. 'mikropml' implements the ML pipeline described by Topçuoğlu et al. (2020) <doi:10.1128/mBio.00434-20> with reasonable default options for data preprocessing, hyperparameter tuning, cross-validation, testing, model evaluation, and interpretation steps. See the website <https://www.schlosslab.org/mikropml/> for more information, documentation, and examples.
Getting started
Browse package contents
Package details |
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| Author | Begüm Topçuoğlu [aut] (<https://orcid.org/0000-0003-3140-537X>), Zena Lapp [aut] (<https://orcid.org/0000-0003-4674-2176>), Kelly Sovacool [aut, cre] (<https://orcid.org/0000-0003-3283-829X>), Evan Snitkin [aut] (<https://orcid.org/0000-0001-8409-278X>), Jenna Wiens [aut] (<https://orcid.org/0000-0002-1057-7722>), Patrick Schloss [aut] (<https://orcid.org/0000-0002-6935-4275>), Nick Lesniak [ctb] (<https://orcid.org/0000-0001-9359-5194>), Courtney Armour [ctb] (<https://orcid.org/0000-0002-5250-1224>), Sarah Lucas [ctb] (<https://orcid.org/0000-0003-1676-5801>) |
| Maintainer | Kelly Sovacool <sovacool@umich.edu> |
| License | MIT + file LICENSE |
| Version | 1.6.1 |
| URL | https://www.schlosslab.org/mikropml/ https://github.com/SchlossLab/mikropml |
| Package repository | View on CRAN |
| Installation |
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