ranger v0.12.1

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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.

Functions in ranger

Name Description
importance.ranger ranger variable importance
print.ranger Print Ranger
print.ranger.forest Print Ranger forest
timepoints.ranger.prediction Ranger timepoints
timepoints.ranger Ranger timepoints
predictions.ranger.prediction Ranger predictions
print.ranger.prediction Print Ranger prediction
ranger Ranger
holdoutRF Hold-out random forests
getTerminalNodeIDs Get terminal node IDs (deprecated)
predict.ranger.forest Ranger prediction
predictions.ranger Ranger predictions
importance_pvalues ranger variable importance p-values
csrf Case-specific random forests.
predict.ranger Ranger prediction
parse.formula Parse formula
treeInfo Tree information in human readable format
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Details

Type Package
Date 2020-01-10
License GPL-3
LinkingTo Rcpp, RcppEigen
Encoding UTF-8
RoxygenNote 7.0.2
URL https://github.com/imbs-hl/ranger
BugReports https://github.com/imbs-hl/ranger/issues
NeedsCompilation yes
Packaged 2020-01-10 10:12:51 UTC; wright
Repository CRAN
Date/Publication 2020-01-10 17:50:05 UTC

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