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.
Downloads:
Reverse dependencies:
Reverse depends: |
Boruta, metaforest |
Reverse imports: |
abcrf, AmyloGram, breakDown, healthcareai, iqspr, missRanger, MlBayesOpt, mopa, OOBCurve, quantregRanger, SCORPIUS, Seurat, simPop, tsensembler |
Reverse suggests: |
batchtools, bWGR, cattonum, climbeR, edarf, forestControl, GSIF, IPMRF, knockoff, MFKnockoffs, mlr, pdp, purge, stranger, SuperLearner |
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=ranger
to link to this page.