https://CRAN.R-project.org/package=mlexperiments> with additional machine learning ('ML') learners. The package provides R6-based learners for the following algorithms: 'glmnet' <https://CRAN.R-project.org/package=glmnet>, 'ranger' <https://CRAN.R-project.org/package=ranger>, 'xgboost' <https://CRAN.R-project.org/package=xgboost>, and 'lightgbm' <https://CRAN.R-project.org/package=lightgbm>. These can be used directly with the 'mlexperiments' R package.">

mllrnrs: R6-Based ML Learners for 'mlexperiments' (original) (raw)

Enhances 'mlexperiments' <https://CRAN.R-project.org/package=mlexperiments> with additional machine learning ('ML') learners. The package provides R6-based learners for the following algorithms: 'glmnet' <https://CRAN.R-project.org/package=glmnet>, 'ranger' <https://CRAN.R-project.org/package=ranger>, 'xgboost' <https://CRAN.R-project.org/package=xgboost>, and 'lightgbm' <https://CRAN.R-project.org/package=lightgbm>. These can be used directly with the 'mlexperiments' R package.

Version: 0.0.6
Depends: R (≥ 4.1.0)
Imports: data.table, kdry, mlexperiments (≥ 0.0.6), R6, stats
Suggests: glmnet, lightgbm (≥ 4.0.0), lintr, measures, mlbench, ParBayesianOptimization, quarto, ranger, splitTools, testthat (≥ 3.0.1), xgboost
Published: 2025-09-08
DOI: 10.32614/CRAN.package.mllrnrs
Author: Lorenz A. Kapsner ORCID iD [cre, aut, cph]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner at gmail.com>
BugReports: https://github.com/kapsner/mllrnrs/issues
License: GPL (≥ 3)
URL: https://github.com/kapsner/mllrnrs
NeedsCompilation: no
SystemRequirements: Quarto command line tools (https://github.com/quarto-dev/quarto-cli).
CRAN checks: mllrnrs results

Documentation:

Reference manual: mllrnrs.html , <mllrnrs.pdf>
Vignettes: glmnet: Binary Classification (source, R code) glmnet: Multiclass Classification (source, R code) glmnet: Regression (source, R code) lightgbm: Binary Classification (source, R code) lightgbm: Multiclass Classification (source, R code) lightgbm: Regression (source, R code) ranger: Binary Classification (source, R code) ranger: Multiclass Classification (source, R code) ranger: Regression (source, R code) xgboost: Binary Classification (source, R code) xgboost: Multiclass Classification (source, R code) xgboost: Regression (source, R code)

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