FisherEM

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.

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Description file content

Package
FisherEM
Type
Package
Title
The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data
Version
1.5.1
Date
2018-10-11
Author
Charles Bouveyron and Camille Brunet
Maintainer
Charles Bouveyron
Depends
MASS, parallel, elasticnet
Description
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.
License
GPL-2
LazyLoad
yes
NeedsCompilation
no
Packaged
2018-10-11 09:53:28 UTC; bouveyro
Repository
CRAN
Date/Publication
2018-10-11 10:10:07 UTC

install.packages('FisherEM')

1.5.1

2 months ago

Charles Bouveyron

GPL-2

Depends on

MASS, parallel, elasticnet

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