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 (Fast Clustering Using Adaptive Density Peak Detection) is a non-iterative procedure that clusters high dimensional data by finding cluster centers from estimated density peaks. It incorporates multivariate local Gaussian density estimation. The number of clusters as well as bandwidths can either be selected by the user or selected automatically through an internal clustering criterion.
Install the most recent version from github:
## In R do:## Skip this line if you already have devtools installedinstall.packages("devtools")library(devtools)install_github("ethanyxu/ADPclust")library(ADPclust)
OR install the released version from CRAN
## In R do:install.packages("ADPclust")library(ADPclust)
Run on a preloaded data set:
library(ADPclust)data(clust3)# Automatic clusteringans <- adpclust(clust3)plot(ans)summary(ans)# Manual centroids selectionadpclust(clust3, centroids = "user")
For more examples please see the Vignette.