mikropml-package {mikropml} | R Documentation |
mikropml: User-Friendly R Package for Robust Machine Learning Pipelines
Description
mikropml
implements supervised machine learning pipelines using regression,
support vector machines, decision trees, random forest, or gradient-boosted trees.
The main functions are preprocess_data()
to process your data prior to
running machine learning, and run_ml()
to run machine learning.
Authors
Begüm D. Topçuoğlu (ORCID)
Zena Lapp (ORCID)
Kelly L. Sovacool (ORCID)
Evan Snitkin (ORCID)
Jenna Wiens (ORCID)
Patrick D. Schloss (ORCID)
See vignettes
Author(s)
Maintainer: Kelly Sovacool sovacool@umich.edu (ORCID)
Authors:
Begüm Topçuoğlu topcuoglu.begum@gmail.com (ORCID)
Zena Lapp zenalapp@umich.edu (ORCID)
Evan Snitkin (ORCID)
Jenna Wiens (ORCID)
Patrick Schloss pschloss@umich.edu (ORCID)
Other contributors:
Nick Lesniak nlesniak@umich.edu (ORCID) [contributor]
Courtney Armour armourc@umich.edu (ORCID) [contributor]
Sarah Lucas salucas@umich.edu (ORCID) [contributor]
See Also
Useful links:
Report bugs at https://github.com/SchlossLab/mikropml/issues