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