FisherEM: The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data

The FisherEM algorithm, proposed by Bouveyron & Brunet (2012) <doi:10.1007/s11222-011-9249-9>, is an efficient method for the clustering of high-dimensional data. FisherEM models and clusters the data in a discriminative and low-dimensional latent subspace. It also provides a low-dimensional representation of the clustered data. A sparse version of Fisher-EM algorithm is also provided.

Version:	1.6
Depends:	MASS, parallel, elasticnet, ggplot2
Imports:	ellipse, plyr
Suggests:	testthat, aricode
Published:	2020-09-28
Author:	Charles Bouveyron, Camille Brunet & Nicolas Jouvin.
Maintainer:	Charles Bouveyron <charles.bouveyron at gmail.com>
License:	GPL-2
NeedsCompilation:	no
Citation:	FisherEM citation info
CRAN checks:	FisherEM results

Documentation:

Reference manual:

FisherEM.pdf

Downloads:

Package source:	FisherEM_1.6.tar.gz
Windows binaries:	r-devel: FisherEM_1.6.zip, r-release: FisherEM_1.6.zip, r-oldrel: FisherEM_1.6.zip
macOS binaries:	r-release (arm64): FisherEM_1.6.tgz, r-oldrel (arm64): FisherEM_1.6.tgz, r-release (x86_64): FisherEM_1.6.tgz, r-oldrel (x86_64): FisherEM_1.6.tgz
Old sources:	FisherEM archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=FisherEM to link to this page.