ADPclust 0.7

Fast Clustering Using Adaptive Density Peak Detection

Released Oct 15, 2016 by Yifan (Ethan) Xu

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knitr 1.14 dplyr 0.5.0 fields 8.4-1 cluster 2.0.5

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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This package was last tested against Renjin 0.8.2500 on Oct 27, 2017.



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