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kapsner
mlexperiments:Machine Learning Experiments
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.
Maintained by Lorenz A. Kapsner. Last updated 30 days ago.
cross-validationexperimenthyperparameter-optimizationhyperparameter-tuningmachine-learningnested
5 stars 7.64 score 49 scripts 2 dependents