clust10


1000 5-dim points in 10 clusters. Generated from the genRandomClust() function of the "clusterGeneration" package with separation value 0.2.


datasets

An implementation of ADPclust clustering procedures (Fast
Clustering Using Adaptive Density Peak Detection). The work is built and
improved upon Rodriguez and Laio[2014]'s idea. 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 an user interactive algorithm that allows the user
to manually selects cluster centroids from a two dimensional "density-distance
plot".

clust10: 1000 5-dim points scattered in 10 clusters

Description

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