LDATree: Oblique Classification Trees with Uncorrelated Linear Discriminant Analysis Splits

A classification tree method that uses Uncorrelated Linear Discriminant Analysis (ULDA) for variable selection, split determination, and model fitting in terminal nodes. It automatically handles missing values and offers visualization tools. For more details, see Wang (2024) <doi:10.48550/arXiv.2410.23147>.

Version:	0.2.0
Imports:	folda, ggplot2, grDevices, magrittr, stats, utils, visNetwork
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2024-10-31
DOI:	10.32614/CRAN.package.LDATree
Author:	Siyu Wang [aut, cre, cph]
Maintainer:	Siyu Wang <iamwangsiyu at gmail.com>
BugReports:	https://github.com/Moran79/LDATree/issues
License:	MIT + file LICENSE
URL:	https://github.com/Moran79/LDATree, http://iamwangsiyu.com/LDATree/
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	LDATree results

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