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>.
|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)|
|Author:||Riccardo Giubilei [aut, cre], Tullia Padellini [aut], Pierpaolo Brutti [aut], Marco Brandi [ctb], Gabriel Nespoli [ctb], Torsten Hothorn [ctb] ((partykit author)), Achim Zeileis [ctb] ((partykit author))|
|Maintainer:||Riccardo Giubilei <riccardogbl at gmail.com>|
|CRAN checks:||etree results|
eforest(): Random Forests With Energy Trees as Base Learners
etree: Classification and Regression With Structured and Mixed-Type Data
|Windows binaries:||r-devel: etree_0.1.0.zip, r-release: etree_0.1.0.zip, r-oldrel: etree_0.1.0.zip|
|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|
Please use the canonical form https://CRAN.R-project.org/package=etree to link to this page.