ranger: A Fast Implementation of Random Forests

A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') can be directly analyzed.

Getting started

Package details

AuthorMarvin N. Wright [aut, cre], Stefan Wager [ctb], Philipp Probst [ctb]
MaintainerMarvin N. Wright <cran@wrig.de>
URL http://imbs-hl.github.io/ranger/ https://github.com/imbs-hl/ranger
Package repositoryView on CRAN
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ranger documentation built on Nov. 13, 2023, 1:09 a.m.