Installation
About
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.
Citation | ranger citation info |
imbs-hl.github.io/ranger/ | |
github.com/imbs-hl/ranger | |
Bug report | File report |
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Depends
R | ≥ 3.1 |