Section: New Software and Platforms

VSURF

Variable Selection Using Random Forests

Keywords: Classification - Statistics - Machine learning - Regression

Functional Description: An R package for Variable Selection Using Random Forests. Available on CRAN, this package performs an automatic (meaning completely data-driven) variable selection procedure. Originally designed to deal with high dimensional data, it can also be applied to standard datasets.

Release Functional Description: * add RFimplem parameter which allows to choose between randomForest, ranger and Rborist to compute random forests predictors. This can be a vector of length 3 to chose a different implementation for each step of VSURF() * update of the parallel and clusterType parameters to also give the possibility to choose which step to perform in parallel with a clusterType per step * add progress bars and information of the progress of the algorithm, and also an estimated computational time for each step

• Contact: Robin Genuer

• URL: https://github.com/robingenuer/VSURF