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') can be directly analyzed.
||abcrf, AmyloGram, healthcareai, OOBCurve, simPop
||batchtools, bWGR, climbeR, edarf, GSIF, mlr, pdp, purge
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