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
DOI: 10.32614/CRAN.package.FisherEM
Author: Charles Bouveyron, Camille Brunet & Nicolas Jouvin.
Maintainer: Charles Bouveyron <charles.bouveyron at>
License: GPL-2
NeedsCompilation: no
Citation: FisherEM citation info
CRAN checks: FisherEM results


Reference manual: FisherEM.pdf


Package source: FisherEM_1.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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