2 packages on CRAN
Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.
Performs simultaneous hyperparameter tuning and feature selection through both single-objective and multi-objective optimization as described in Binder, Moosbauer et al. (2019) <arXiv:1912.12912>. Uses the 'ecr'-package as basis but adds mixed integer evolutionary strategies and multi-fidelity functionality as well as operators specific for the problem of feature selection.