The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data R package FisherEM version 1.6 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. Software Depends: MASS, parallel, elasticnet, ggplot2 Imports: ellipse, plyr Suggests: testthat, aricode Charles Bouveyron <charles.bouveyron@gmail.com> Comprehensive R Archive Network (CRAN) Charles Bouveyron, Camille Brunet & Nicolas Jouvin. GPL-2 2020-09-28 application/tgz https://CRAN.R-project.org/package=FisherEM doi:10.32614/CRAN.package.FisherEM