General purpose R package with helper functions.
Allows you to describe parameters with type informations and constrains, build sets of such parameters, sample from them, build statistical designs, etc. This is used in mlr to describe machine learning algorithm parameters, for other people its mainly useful to quickly generate LHS designs for arbitrary parameter spaces.
Several R packages for using various (supervised) machine learning algorithms in R. Facilities for tuning, feature selection, algorithm extension and parallelization are included. Currently hosted at R-Forge.
Two R packages for efficient batch computing with R.
Collection of single objective optimization test functions for benchmarks and optimizer development. Mainly written by Olaf Mersmann.
Instance feature calculation and evolutionary instance generation for the traveling salesman problem.