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densityClust
View on CRAN: Click
here
Download and install densityClust package within the R console
Install from CRAN:
install.packages("densityClust")
Install from Github:
library("remotes")
install_github("cran/densityClust") Install by package version:
library("remotes")
install_version("densityClust", "0.3.3") Attach the package and use:
library("densityClust")
Maintained by
Thomas Lin Pedersen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-07-21
Latest Update: 2024-01-29
Description:
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.
How to cite:
Thomas Lin Pedersen (2014). densityClust: Clustering by Fast Search and Find of Density Peaks. R package version 0.3.3, https://cran.r-project.org/web/packages/densityClust. Accessed 05 Mar. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for densityClust
Functions, R codes and Examples using
the densityClust R package
Some associated functions: clustered . clusters . densityClust-package . densityClust . estimateDc . findClusters . plotDensityClust . plotMDS . plotTSNE .
Some associated R codes: cpp11.R . densityClust-package.R . densityClust.R . plotDensityClust.R . Full densityClust package functions and examples
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