leaderCluster: Leader Clustering Algorithm

The leader clustering algorithm provides a means for clustering a set of data points. Unlike many other clustering algorithms it does not require the user to specify the number of clusters, but instead requires the approximate radius of a cluster as its primary tuning parameter. The package provides a fast implementation of this algorithm in n-dimensions using Lp-distances (with special cases for p=1,2, and infinity) as well as for spatial data using the Haversine formula, which takes latitude/longitude pairs as inputs and clusters based on great circle distances.

Version: 1.2
Published: 2014-12-16
Author: Taylor B. Arnold
Maintainer: Taylor B. Arnold <taylor.arnold at acm.org>
License: LGPL-2
NeedsCompilation: yes
CRAN checks: leaderCluster results


Reference manual: leaderCluster.pdf
Package source: leaderCluster_1.2.tar.gz
Windows binaries: r-devel: leaderCluster_1.2.zip, r-release: leaderCluster_1.2.zip, r-oldrel: leaderCluster_1.2.zip
OS X El Capitan binaries: r-release: leaderCluster_1.2.tgz
OS X Mavericks binaries: r-oldrel: leaderCluster_1.2.tgz


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