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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("FisherEM")

1.5.1 by Charles Bouveyron, 2 months ago


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


Authors: Charles Bouveyron and Camille Brunet


Documentation:   PDF Manual  


Task views:


GPL-2 license


Depends on MASS, parallel, elasticnet


See at CRAN