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FisherEM (version 1.6)

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.

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Version

Install

install.packages('FisherEM')

Monthly Downloads

274

Version

1.6

License

GPL-2

Maintainer

Charles Bouveyron

Last Published

September 28th, 2020

Functions in FisherEM (1.6)

print.fem

The print function for 'fem' objects.
bfem

The Bayesian Fisher-EM algorithm.
fem.ari

Adjusted Rand index
plot.bfem

Plotting function
FisherEM-package

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

The sparse Fisher-EM algorithm
fem

The Fisher-EM algorithm
plot.fem

The plot function for 'fem' objects.
simu_bfem

Experimental setting of the chapter BFEM