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.
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Description file content
- Package
- ranger
- Type
- Package
- Title
- A Fast Implementation of Random Forests
- Version
- 0.11.2
- Date
- 2019-03-07
- Author
- Marvin N. Wright [aut, cre], Stefan Wager [ctb], Philipp Probst [ctb]
- Maintainer
- Marvin N. Wright
- Description
- 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.
- License
- GPL-3
- Imports
- Rcpp (>= 0.11.2), Matrix
- LinkingTo
- Rcpp, RcppEigen
- Depends
- R (>= 3.1)
- Suggests
- survival, testthat
- RoxygenNote
- 6.1.1
- URL
- BugReports
- https://github.com/imbs-hl/ranger/issues
- NeedsCompilation
- yes
- Packaged
- 2019-03-07 12:01:18 UTC; wright
- Repository
- CRAN
- Date/Publication
- 2019-03-07 14:10:20 UTC
install.packages('ranger')
0.11.2
2 months ago
https://github.com/imbs-hl/ranger
Marvin N. Wright
GPL-3
Depends on
R (>= 3.1)