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

The FisherEM algorithm, proposed by Bouveyron & Brunet (2012) , 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.


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install.packages("FisherEM")

1.6 by Charles Bouveyron, a month ago


Browse source code at https://github.com/cran/FisherEM


Authors: Charles Bouveyron , Camille Brunet & Nicolas Jouvin.


Documentation:   PDF Manual  


Task views:


GPL-2 license


Imports ellipse, plyr

Depends on MASS, parallel, elasticnet, ggplot2

Suggests testthat, aricode


See at CRAN