Oblique Classification Trees with Uncorrelated Linear Discriminant Analysis Splits
Overview
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.
- Change the splitting rule to a multi-way split based on LDA.
- Integrate the ULDA and forward ULDA from the
foldapackage. - Move most of the utils function to the
foldapackage. - Updates in the pruning process: progress bar, new test statistics, ...
- Support downsampling.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 4 (1 internal)includes a package overview page
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 25%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
Releases over time
8 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/moran79/ldatree on 2026-10-18.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2024-10-31 · The repository has a site deploy workflow
pkgdown site last built 2024-10-31
Dependencies
Installing LDATree adds 44 packages (23 with compiled code, 39 MB of source tarballs). Heaviest: ggplot2 6.0 MB, bslib 5.6 MB, visNetwork 4.1 MB.
Code & Tests
People & History
Package metadata
- First published
- 2023-08-22
- Total releases
- 4 / 3 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 1.3 MB
Cite
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