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.


Reference manual

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1.6 by Charles Bouveyron, a year ago

Browse source code at

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