Package: etree 0.1.0

etree: Classification and Regression with Structured and Mixed-Type Data

Implementation of Energy Trees, a statistical model to perform classification and regression with structured and mixed-type data. The model has a similar structure to Conditional Trees, but brings in Energy Statistics to test independence between variables that are possibly structured and of different nature. Currently, the package covers functions and graphs as structured covariates. It builds upon 'partykit' to provide functionalities for fitting, printing, plotting, and predicting with Energy Trees. Energy Trees are described in Giubilei et al. (2022) <arxiv:2207.04430>.

Authors:Riccardo Giubilei [aut, cre], Tullia Padellini [aut], Pierpaolo Brutti [aut], Marco Brandi [ctb], Gabriel Nespoli [ctb], Torsten Hothorn [ctb], Achim Zeileis [ctb]

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# Install 'etree' in R:
install.packages('etree', repos = c('https://ricgbl.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ricgbl/etree/issues

Datasets:

On CRAN:

4.52 score 3 stars 11 scripts 207 downloads 7 exports 89 dependencies

Last updated 2 years agofrom:190143c708. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-winNOTENov 13 2024
R-4.5-linuxNOTENov 13 2024
R-4.4-winNOTENov 13 2024
R-4.4-macNOTENov 13 2024
R-4.3-winOKNov 13 2024
R-4.3-macOKNov 13 2024

Exports:depthdist_compeforestetreenodeapplynodeidswidth

Dependencies:abindashBHbitopsbootbrainGraphcliclustercodacodetoolscolorspacecpp11data.tabledeSolvedoParallelenergyevaluatefansifarverfdafda.uscfdsFNNforeachFormulaggplot2gluegraphongslgtablehdrcdehighrigraphinumisobanditeratorskernlabKernSmoothknitrkskSampleslabelinglatticelibcoinlifecyclelocfitmagrittrMASSMatrixmclustmgcvmulticoolmunsellmvtnormnetworkNetworkDistancenlmepartykitpcaPPpermutepillarpkgconfigpracmaR6rainbowrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRCurlRdpackrlangROptSpacerpartRSpectrascalesstatnet.commonSuppDistssurvivalTDAtibbleusedistutf8vctrsviridisLitewithrxfunyaml

eforest(): Random Forests With Energy Trees as Base Learners

Rendered frometree-vignette-eforest.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2022-07-12
Started: 2022-07-04

etree: Classification and Regression With Structured and Mixed-Type Data

Rendered frometree-vignette.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2022-07-12
Started: 2022-04-22

Readme and manuals

Help Manual

Help pageTopics
etree: Classification and Regression With Structured and Mixed-Type Dataetree-package
Classification toy datasetdata_cls
Regression toy datasetdata_reg
Distancesdist_comp
Energy Forestseforest
Energy Treeetree
Methods for "etree" objects"[.etree" "[[.etree" depth.etree depth.party etree-methods length.etree length.party print.etree width.etree width.party [.etree [[.etree
Size of Energy Treesdepth etree-size width
Apply functions over nodesnodeapply nodeapply.etree nodeapply.party nodeapply.partynode
Extract node identifiers.nodeids nodeids.etree nodeids.party nodeids.partynode
Visualization of Energy Treesplot.etree
Predictions for Energy Forestspredict.eforest
Predictions for Energy Treespredict.etree