ADPclust 0.7

Fast Clustering Using Adaptive Density Peak Detection

Released Oct 15, 2016 by Yifan (Ethan) Xu [aut, cre], Xiao-Feng Wang [aut]

This package cannot yet be used with Renjin it depends on other packages which are not available: dplyr 0.5.0 and knitr 1.14


knitr 1.14 dplyr 0.5.0 cluster 2.0.5 fields 8.4-1

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:



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