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ADPclust  

Fast Clustering Using Adaptive Density Peak Detection
View on CRAN: Click here


Download and install ADPclust package within the R console
Install from CRAN:
install.packages("ADPclust")

Install from Github:
library("remotes")
install_github("cran/ADPclust")

Install by package version:
library("remotes")
install_version("ADPclust", "0.7")



Attach the package and use:
library("ADPclust")
Maintained by
Yifan (Ethan) Xu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-04-20
Latest Update: 2016-10-15
Description:
An implementation of ADPclust clustering procedures (Fast Clustering Using Adaptive Density Peak Detection). The work is built and improved upon the idea of Rodriguez and Laio (2014). ADPclust clusters data by finding density peaks in a density-distance plot generated from local multivariate Gaussian density estimation. It includes an automatic centroids selection and parameter optimization algorithm, which finds the number of clusters and cluster centroids by comparing average silhouettes on a grid of testing clustering results; It also includes a user interactive algorithm that allows the user to manually selects cluster centroids from a two dimensional "density-distance plot". Here is the research article associated with this package: "Wang, Xiao-Feng, and Yifan Xu (2015) Fast clustering using adaptive density peak detection." Statistical methods in medical research". url: http://smm.sagepub.com/content/early/2015/10/15/0962280215609948.abstract.
How to cite:
Yifan (Ethan) Xu (2015). ADPclust: Fast Clustering Using Adaptive Density Peak Detection. R package version 0.7, https://cran.r-project.org/web/packages/ADPclust. Accessed 27 Oct. 2026.
Previous versions and publish date:
0.6.3 (2015-04-20 14:17), 0.6.5 (2015-12-03 17:44), 0.7 (2016-10-15 11:37), (2026-07-09 07:56)
Other packages that cited ADPclust R package
View ADPclust citation profile
Other R packages that ADPclust depends, imports, suggests or enhances
Complete documentation for ADPclust
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