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.
| Reverse depends: |
causalweight, Iscores, metaforest, PKLMtest, RfEmpImp, tuneRanger |
| Reverse imports: |
abcrf, ADAPTS, alookr, AmpGram, AmyloGram, BioMM, Boruta, CancerGram, CausalGPS, CornerstoneR, decoupleR, drpop, dynfeature, fairadapt, finetune, gapclosing, genphen, GRPtests, healthcareai, hpiR, htmldf, hypoRF, influential, landmap, memoria, miceRanger, missRanger, mistyR, mlr3shiny, MSiP, multiclassPairs, OOBCurve, orf, outForest, poolVIM, PrInCE, quantregRanger, radiant.model, randomForestExplainer, RaSEn, RCAS, REMP, rfinterval, RFpredInterval, riskRegression, rmweather, RNAmodR.ML, sambia, SCORPIUS, simPop, soilassessment, solitude, spatialRF, spm, spm2, SPOT, stablelearner, StratifiedMedicine, synthpop, tbma, tsensembler, VIM, VSURF, worcs |
| Reverse suggests: |
arenar, batchtools, biotmle, breakDown, butcher, cattonum, corrgrapher, DALEX, DoubleML, drifter, DriveML, dynwrap, ENMTools, fairmodels, fastshap, flashlight, forestControl, HPiP, HPLB, iBreakDown, iml, Infusion, ingredients, IPMRF, knockoff, lime, lmtp, MachineShop, mcboost, microbiomeMarker, mlr, mlr3learners, mlr3tuningspaces, mlr3viz, mlrCPO, mlrintermbo, modelDown, modelplotr, modelStudio, nlpred, parsnip, pdp, piRF, purge, r2pmml, sense, shapr, sperrorest, splitTools, SSLR, stacks, SuperLearner, superml, text, tidypredict, topdownr, tree.interpreter, triplot, txshift, varImp, vimp, vip, vivid |