Model-Based Clustering in the Fisher Discriminative Subspace
J.Loisel T.Souvannarath M.Tchebanenko C.Bouveyron C.Brunet
Who to complain to <thanh.souvannarath@gmail.com>
Model-Based Clustering in the Fisher Discriminative
Subspace provides a low-dimensional discriminative
representation of the clustered data. To find a parsimonious
and discriminative fit for the data this method uses
discriminative latent model (DLM). The Fisher EM algorithm
estimates the parameters of DLM models in order to cluster and
visualize the clustered data.

The FisherEM package provides an efficient algorithm for
the unsupervised classification of high-dimensional data. This
FisherEM algorithm models and clusters the data in a
discriminative and low-dimensional latent subspace. It also
provides a low-dimensional representation of the clustered
data.

The FisherEM package provides an efficient algorithm for
the unsupervised classification of high-dimensional data. This
FisherEM algorithm 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.

The FisherEM Algorithm to Simultaneously Cluster and Visualize
High-Dimensional Data
The FisherEM algorithm, proposed by Bouveyron & Brunet (201) <doi:10.1007/s11222-011-9249-9>,
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.

Charles Bouveyron, Camille Brunet & Nicolas Jouvin.
The FisherEM algorithm, proposed by Bouveyron & Brunet (2012) <doi:10.1007/s11222-011-9249-9>,
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.