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>.

Version: 0.1.0
Depends: R (≥ 3.7.0)
Imports: brainGraph, cluster, energy, fda.usc (≥ 2.0.0), igraph, NetworkDistance, parallel, partykit, survival, TDA, usedist
Suggests: knitr, MLmetrics, rmarkdown, testthat (≥ 3.0.0)
Published: 2022-07-16
Author: Riccardo Giubilei ORCID iD [aut, cre], Tullia Padellini [aut], Pierpaolo Brutti [aut], Marco Brandi [ctb], Gabriel Nespoli [ctb], Torsten Hothorn ORCID iD [ctb] ((partykit author)), Achim Zeileis ORCID iD [ctb] ((partykit author))
Maintainer: Riccardo Giubilei <riccardogbl at>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: etree results


Reference manual: etree.pdf
Vignettes: eforest(): Random Forests With Energy Trees as Base Learners
etree: Classification and Regression With Structured and Mixed-Type Data


Package source: etree_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): etree_0.1.0.tgz, r-oldrel (arm64): etree_0.1.0.tgz, r-release (x86_64): etree_0.1.0.tgz, r-oldrel (x86_64): etree_0.1.0.tgz


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