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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 |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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