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.

Documentation

Manual: ADPclust.pdf
Vignette: ADPclust-vignette

Maintainer: Yifan (Ethan) Xu <ethan.yifanxu at gmail.com>

Author(s): Yifan (Ethan) Xu*, Xiao-Feng Wang*

Install package and any missing dependencies by running this line in your R console:

install.packages("ADPclust")

Depends R (>= 3.0.0),
Imports dplyr, cluster, fields, knitr
Suggests rmarkdown, testthat
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Package ADPclust
Materials
URL https://github.com/ethanyxu/ADPclust
Task Views Cluster
Version 0.7
Published 2016-10-15
License GPL (>= 2)
BugReports https://github.com/ethanyxu/ADPclust/issues
SystemRequirements
NeedsCompilation no
Citation
CRAN checks ADPclust check results
Package source ADPclust_0.7.tar.gz