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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.

copied from cf-staging / r-ranger
Label Latest Version
main 0.17.0
cf201901 0.10.1
cf202003 0.12.1
gcc7 0.10.1

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