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) with reasonable default options for data preprocessing, hyperparameter tuning, cross-validation, testing, model evaluation, and interpretation steps. See the website <> for more information, documentation, and examples.


Reference manual

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1.2.0 by Kelly Sovacool, 16 days ago,

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Browse source code at

Authors: Begüm Topçuoğlu [aut] , Zena Lapp [aut] , Kelly Sovacool [aut, cre] , Evan Snitkin [aut] , Jenna Wiens [aut] , Patrick Schloss [aut] , Nick Lesniak [ctb] , Courtney Armour [ctb] , Sarah Lucas [ctb]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports caret, dplyr, e1071, glmnet, kernlab, MLmetrics, randomForest, rlang, rpart, stats, utils, xgboost

Suggests doFuture, foreach, future, future.apply, ggplot2, knitr, progress, progressr, purrr, rmarkdown, testthat, tidyr

See at CRAN