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

The FisherEM algorithm, proposed by Bouveyron & Brunet (201) , 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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1.5.1 by Charles Bouveyron, 2 years ago

Browse source code at

Authors: Charles Bouveyron and Camille Brunet

Documentation:   PDF Manual  

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GPL-2 license

Depends on MASS, parallel, elasticnet

See at CRAN