FisherEM (1.5.1)

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.

Maintainer: Charles Bouveyron
Author(s): Charles Bouveyron and Camille Brunet

License: GPL-2

Uses: elasticnet, MASS

Released over 1 year ago.