Provides 'R6' objects to perform parallelized hyperparameter optimization and cross-validation. Hyperparameter optimization can be performed with Bayesian optimization (via 'ParBayesianOptimization' <https://cran.r-project.org/package=ParBayesianOptimization>) and grid search. The optimized hyperparameters can be validated using k-fold cross-validation. Alternatively, hyperparameter optimization and validation can be performed with nested cross-validation. While 'mlexperiments' focuses on core wrappers for machine learning experiments, additional learner algorithms can be supplemented by inheriting from the provided learner base class.
Version: 0.0.5 Depends: R (≥ 4.1.0) Imports: data.table, kdry, parallel, progress, R6, splitTools, stats Suggests: class, datasets, lintr, mlbench, mlr3measures, ParBayesianOptimization, quarto, rpart, testthat (≥ 3.0.1) Published: 2025-03-03 DOI: 10.32614/CRAN.package.mlexperiments Author: Lorenz A. Kapsner [cre, aut, cph] Maintainer: Lorenz A. Kapsner <lorenz.kapsner at gmail.com> BugReports: https://github.com/kapsner/mlexperiments/issues License: GPL (≥ 3) URL: https://github.com/kapsner/mlexperiments NeedsCompilation: no SystemRequirements: Quarto command line tools (https://github.com/quarto-dev/quarto-cli). CRAN checks: mlexperiments results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=mlexperiments to link to this page.
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