Recursive Partitioning and Regression Trees

Recursive partitioning for classification, regression and survival trees. An implementation of most of the functionality of the 1984 book by Breiman, Friedman, Olshen and Stone.


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This is the source code for the rpart package, which is a recommended package in R. It gets posted to the comprehensive R archive (CRAN) as needed after undergoing a thorough testing.

Overview

The rpart code builds classification or regression models of a very general structure using a two stage procedure; the resulting models can be represented as binary trees. The package implements many of the ideas found in the CART (Classification and Regression Trees) book and programs of Breiman, Friedman, Olshen and Stone. Because CART is the trademarked name of a particular software implementation of these ideas and tree was used for the Splus routines of Clark and Pregibon, a different acronym - Recursive PARTitioning or rpart - was chosen.

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Reference manual

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install.packages("rpart")

4.1-15 by Beth Atkinson, 3 months ago


https://github.com/bethatkinson/rpart, https://cran.r-project.org/package=rpart


Report a bug at https://github.com/bethatkinson/rpart/issues


Browse source code at https://github.com/cran/rpart


Authors: Terry Therneau [aut] , Beth Atkinson [aut, cre] , Brian Ripley [trl] (producer of the initial R port , maintainer 1999-2017)


Documentation:   PDF Manual  


Task views: Analysis of Ecological and Environmental Data, Machine Learning & Statistical Learning, Multivariate Statistics, Survival Analysis


GPL-2 | GPL-3 license


Depends on graphics, stats, grDevices

Suggests survival


Imported by BCA, Biocomb, C443, CADStat, CORElearn, CTShiny, DMwR, DMwR2, Dforest, EZtune, FFTrees, HMP, Harvest.Tree, Hmisc, JOUSBoost, LTRCtrees, MachineLearning, MergeGUI, MetabolomicsBasics, Modeler, NoiseFiltersR, OptimClassifier, PredPsych, RecordLinkage, SSDM, SubgrpID, TSDT, TextForecast, VSURF, aVirtualTwins, autoBagging, binst, biomod2, bnclassify, bst, chemmodlab, creditmodel, dlookr, ebmc, explore, exprso, fastAdaboost, featurefinder, galgo, gamclass, gencve, hybridEnsemble, ibmdbR, ipred, mcca, mfe, mice, mopa, partykit, pre, predictoR, psica, radiant.model, regressoR, rminer, rms, rotationForest, semtree, simputation, smartR, sperrorest, statip, supclust, synthpop, tree.bins, varbin, vcrpart, visTree.

Depended on by AntAngioCOOL, DStree, DidacticBoost, GENEAclassify, GPLTR, MplusTrees, NHEMOtree, PSAgraphics, REEMtree, SQB, ada, adabag, chemometrics, dtree, fda.usc, gamlss.add, iBST, jlctree, longRPart2, maboost, maptree, metacart, multiPIM, quint, regclass, rpart.plot, rpart.utils, rpartScore, spatstat, spc4sts, splinetree, stima, treeClust.

Suggested by BatchExperiments, BiodiversityR, CALIBERrfimpute, ChemometricsWithR, DAAG, DynTxRegime, FRESA.CAD, FSelector, FSelectorRcpp, GSIF, HSAUR, HSAUR2, HSAUR3, HandTill2001, LocalControl, MachineShop, MatchIt, ModelGood, OpenML, PivotalR, R2HTML, ROSE, StratifiedMedicine, SuperLearner, UBL, animint2, arsenal, aslib, aurelius, batchtools, caTools, candisc, caret, caretEnsemble, catdata, ceterisParibus, classifly, compboost, crtests, dials, doParallel, doSNOW, e1071, evtree, flacco, fscaret, ggResidpanel, ggdendro, ggplot2, iml, imputeR, klaR, languageR, lulcc, mboost, medflex, memoria, metaheur, mlr, mlrCPO, mlrMBO, mosaicModel, naniar, parsnip, partools, pdp, pec, plotmo, pmml, preprocomb, purge, rattle, recipes, riskRegression, shapper, shipunov, smartdata, stablelearner, tidyrules, utiml, vip, visNetwork.

Enhanced by d3r, dendextend, prediction, sfsmisc.


See at CRAN