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mlexperiments
View on CRAN: Click
here
Download and install mlexperiments package within the R console
Install from CRAN:
install.packages("mlexperiments")
Install from Github:
library("remotes")
install_github("cran/mlexperiments") Install by package version:
library("remotes")
install_version("mlexperiments", "1.0.0") Attach the package and use:
library("mlexperiments")
Maintained by
Lorenz A. Kapsner
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-06-10
Latest Update: 2025-03-03
Description:
Provides 'R6' objects to perform parallelized hyperparameter
optimization and cross-validation. Hyperparameter optimization can be
performed with Bayesian optimization (via '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.
How to cite:
Lorenz A. Kapsner (2023). mlexperiments: Machine Learning Experiments. R package version 1.0.0, https://cran.r-project.org/web/packages/mlexperiments. Accessed 05 Jun. 2026.
Previous versions and publish date:
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Other R packages that mlexperiments depends,
imports, suggests or enhances
Complete documentation for mlexperiments
Functions, R codes and Examples using
the mlexperiments R package
Some associated functions: LearnerGlm . LearnerKnn . LearnerLm . LearnerRpart . MLBase . MLCrossValidation . MLExperimentsBase . MLLearnerBase . MLNestedCV . MLTuneParameters . handle_cat_vars . metric . metric_types_helper . performance . predictions . validate_fold_equality .
Some associated R codes: cv_class_base.R . cv_class_nested.R . cv_helper_base.R . cv_helper_nested.R . cv_performance.R . cv_predictions.R . learner_class_base.R . learner_glm.R . learner_knn.R . learner_lm.R . learner_rpart.R . ml_class_base.R . ml_helper_base.R . optimizer_class_base.R . optimizer_class_bayesian.R . optimizer_class_grid.R . optimizer_helper_base.R . optimizer_helper_bayesian.R . optimizer_helper_grid.R . tune_class_base.R . tune_helper_base.R . utils_eval_params.R . utils_handle_cat_vars.R . utils_method_params_refactor.R . utils_metrics.R . utils_validate_fold_equality.R . zzz.R . Full mlexperiments package functions and examples
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