LDATree: Oblique Classification Trees with Uncorrelated LinearDiscriminant 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 + fileLICENSE |
| URL: | https://github.com/Moran79/LDATree,http://iamwangsiyu.com/LDATree/ |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | LDATree results |
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