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 |
imports | Matrix , Rcpp (>= 0.11.2) |
depends | R (>= 3.1) |
linkingto | RcppEigen |
suggests | survival , testthat |
Contributors | Stefan Wager, Marvin Wright, Philipp Probst |
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