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.
| Version: | 1.7.0 | 
| Depends: | R (≥ 4.1.0) | 
| Imports: | caret, dplyr, e1071, glmnet, kernlab, methods, MLmetrics, randomForest, rlang, rpart, S4Vectors, SingleCellExperiment, stats, SummarizedExperiment, tidyselect, TreeSummarizedExperiment, utils, xgboost | 
| Suggests: | assertthat, doFuture, forcats, foreach, furrr, future, future.apply, ggplot2, knitr, progress, progressr, purrr, rmarkdown, roxygen2, rsample, styler, testthat, tidyr, usethis | 
| Published: | 2025-10-29 | 
| DOI: | 10.32614/CRAN.package.mikropml | 
| Author: | Begüm Topçuoğlu | 
| Maintainer: | Kelly Sovacool <sovacool at umich.edu> | 
| BugReports: | https://github.com/SchlossLab/mikropml/issues | 
| License: | MIT + file LICENSE | 
| URL: | https://www.schlosslab.org/mikropml/, https://github.com/SchlossLab/mikropml | 
| NeedsCompilation: | no | 
| Citation: | mikropml citation info | 
| Materials: | README, NEWS | 
| CRAN checks: | mikropml results | 
| Reference manual: | mikropml.html , mikropml.pdf | 
| Vignettes: | Introduction to mikropml (source, R code) mikropml paper (source, R code) | 
| Package source: | mikropml_1.7.0.tar.gz | 
| Windows binaries: | r-devel: mikropml_1.6.2.zip, r-release: mikropml_1.6.2.zip, r-oldrel: mikropml_1.6.2.zip | 
| macOS binaries: | r-release (arm64): mikropml_1.6.2.tgz, r-oldrel (arm64): mikropml_1.7.0.tgz, r-release (x86_64): mikropml_1.6.2.tgz, r-oldrel (x86_64): mikropml_1.6.2.tgz | 
| Old sources: | mikropml archive | 
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