Package: lumbermark 0.9.0.9001

lumbermark: Resistant Clustering via Chopping Up Mutual Reachability Minimum Spanning Trees

Implements a fast and resistant divisive clustering algorithm which identifies a specified number of clusters: 'lumbermark' iteratively chops off sizeable limbs that are joined by protruding segments of a dataset's mutual reachability minimum spanning tree (Gagolewski, 2026 <doi:10.48550/arXiv.2604.07143>). The use of a mutual reachability distance pulls peripheral points farther away from each other. When combined with the 'deadwood' package, it can act as an outlier detector. The 'Python' version of 'lumbermark' is available via 'PyPI'.

Authors:Marek Gagolewski [aut, cre, cph]

lumbermark_0.9.0.9001.tar.gz
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manual.pdf |manual.html
card.svg |card.png
lumbermark/json (API)
NEWS

# Install 'lumbermark' in R:
install.packages('lumbermark', repos = c('https://gagolews.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gagolews/lumbermark/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

anomaly-detectioncluster-analysisclusteringclustering-algorithmhdbscanmachine-learningmachine-learning-algorithmsminimum-spanning-treeminimum-spanning-treesoutlier-detectionoutlierscpp

4.00 score 489 downloads 1 exports 3 dependencies

Last updated from:cdc096eec0. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK99
linux-devel-x86_64OK101
source / vignettesOK186
linux-release-arm64OK95
linux-release-x86_64OK108
macos-release-arm64OK143
macos-release-x86_64OK173
macos-oldrel-arm64OK102
macos-oldrel-x86_64OK180
windows-develOK126
windows-releaseOK119
windows-oldrelOK214
wasm-releaseFAIL95

Exports:lumbermark

Dependencies:deadwoodquitefastmstRcpp

Readme and manuals

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Lumbermark: Fast and Robust Clusteringlumbermark lumbermark.default lumbermark.dist lumbermark.mst