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') can be directly analyzed.

Documentation

Manual: ranger.pdf
Vignette: None available.

Maintainer: Marvin N. Wright <cran at wrig.de>

Author(s): Marvin N. Wright

Install package and any missing dependencies by running this line in your R console:

install.packages("ranger")

Depends R (>= 3.1)
Imports Rcpp(>=0.11.2), Matrix
Suggests survival, testthat, GenABEL
Enhances
Linking to Rcpp, RcppEigen
Reverse
depends
Boruta
Reverse
imports
abcrf, AmyloGram, healthcareai, mopa, OOBCurve, ordinalForest, simPop
Reverse
suggests
batchtools, bWGR, climbeR, edarf, GSIF, mlr, NAM, pdp, purge
Reverse
enhances
Reverse
linking to

Package ranger
Materials
URL https://github.com/imbs-hl/ranger
Task Views MachineLearning , Survival
Version 0.8.0
Published 2017-06-20
License GPL-3
BugReports https://github.com/imbs-hl/ranger/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks ranger check results
Package source ranger_0.8.0.tar.gz