densityClust: Clustering by Fast Search and Find of Density Peaks

An improved implementation (based on k-nearest neighbors) of the density peak clustering algorithm, originally described by Alex Rodriguez and Alessandro Laio (Science, 2014 vol. 344). It can handle large datasets (> 100,000 samples) very efficiently. It was initially implemented by Thomas Lin Pedersen, with inputs from Sean Hughes and later improved by Xiaojie Qiu to handle large datasets with kNNs.

Version: 0.3.3
Imports: FNN, ggplot2, ggrepel, grDevices, gridExtra, RColorBrewer, Rtsne
LinkingTo: cpp11
Suggests: covr, testthat
Published: 2024-01-29
Author: Thomas Lin Pedersen [aut, cre], Sean Hughes [aut], Xiaojie Qiu [aut]
Maintainer: Thomas Lin Pedersen <thomasp85 at gmail.com>
BugReports: https://github.com/thomasp85/densityClust/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/thomasp85/densityClust
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: densityClust results

Documentation:

Reference manual: densityClust.pdf

Downloads:

Package source: densityClust_0.3.3.tar.gz
Windows binaries: r-devel: densityClust_0.3.3.zip, r-release: densityClust_0.3.3.zip, r-oldrel: densityClust_0.3.3.zip
macOS binaries: r-release (arm64): densityClust_0.3.3.tgz, r-oldrel (arm64): densityClust_0.3.3.tgz, r-release (x86_64): densityClust_0.3.3.tgz
Old sources: densityClust archive

Reverse dependencies:

Reverse suggests: FCPS

Linking:

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