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mlexperiments

Machine Learning Experiments

Provides 'R6' objects to perform parallelized hyperparameter optimization and cross-validation. Hyperparameter optimization can be performed with Bayesian optimization (via 'rBayesianOptimization' <https://cran.r-project.org/package=rBayesianOptimization>) 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.

Versions across snapshots

VersionRepositoryFileSize
1.0.0 rolling linux/jammy R-4.5 mlexperiments_1.0.0.tar.gz 690.2 KiB
1.0.0 rolling linux/noble R-4.5 mlexperiments_1.0.0.tar.gz 690.2 KiB
1.0.0 rolling source/ R- mlexperiments_1.0.0.tar.gz 250.6 KiB
1.0.0 latest linux/jammy R-4.5 mlexperiments_1.0.0.tar.gz 690.2 KiB
1.0.0 latest linux/noble R-4.5 mlexperiments_1.0.0.tar.gz 690.2 KiB
1.0.0 latest source/ R- mlexperiments_1.0.0.tar.gz 250.6 KiB
1.0.0 2026-04-26 source/ R- mlexperiments_1.0.0.tar.gz 250.6 KiB
1.0.0 2026-04-23 source/ R- mlexperiments_1.0.0.tar.gz 250.6 KiB
1.0.0 2026-04-09 windows/windows R-4.5 mlexperiments_1.0.0.zip 700.9 KiB
0.0.5 2025-04-20 source/ R- mlexperiments_0.0.5.tar.gz 249.8 KiB

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