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FisherEM: The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data
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.
Getting started
Browse package contents
Package details |
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| Author | Charles Bouveyron, Camille Brunet & Nicolas Jouvin. |
| Maintainer | Charles Bouveyron <charles.bouveyron@gmail.com> |
| License | GPL-2 |
| Version | 1.6 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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