fastcluster: Fast hierarchical clustering routines for R and Python

This is a two-in-one package which provides interfaces to both R and Python. It implements fast hierarchical, agglomerative clustering routines. Part of the functionality is designed as drop-in replacement for existing routines: “linkage” in the SciPy package “scipy.cluster.hierarchy”, “hclust” in R's “stats” package, and the “flashClust” package. It provides the same functionality with the benefit of a much faster implementation. Moreover, there are memory-saving routines for clustering of vector data, which go beyond what the existing packages provide. For information on how to install the Python files, see the file INSTALL in the source distribution.

Version: 1.1.13
Enhances: stats, flashClust
Published: 2013-12-17
Author: Daniel Müllner, http://danifold.net
Maintainer: Daniel Müllner <daniel at danifold.net>
License: FreeBSD | GPL-2 | file LICENSE
URL: http://danifold.net/fastcluster.html
NeedsCompilation: yes
Citation: fastcluster citation info
Materials: README NEWS INSTALL
In views: Cluster
CRAN checks: fastcluster results

Downloads:

Reference manual: fastcluster.pdf
Vignettes: User's manual
Package source: fastcluster_1.1.13.tar.gz
Windows binaries: r-devel: fastcluster_1.1.13.zip, r-release: fastcluster_1.1.13.zip, r-oldrel: fastcluster_1.1.13.zip
OS X Snow Leopard binaries: r-release: fastcluster_1.1.13.tgz, r-oldrel: fastcluster_1.1.13.tgz
OS X Mavericks binaries: r-release: fastcluster_1.1.13.tgz
Old sources: fastcluster archive

Reverse dependencies:

Reverse imports: freqweights, heatmap3, SpatialVx
Reverse suggests: hyperSpec, linkcomm, Rclusterpp