FisherEM: The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data
Version 1.5.1

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.

Package details

AuthorCharles Bouveyron and Camille Brunet
Date of publication2018-10-11 10:10:07 UTC
MaintainerCharles Bouveyron <[email protected]>
LicenseGPL-2
Version1.5.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("FisherEM")

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FisherEM documentation built on Oct. 11, 2018, 5:03 p.m.