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.
- Version1.6
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- FisherEM citation info
- Last release09/28/2020
Team
Charles Bouveyron
Camille Brunet
Nicolas Jouvin
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- Depends3 packages
- Imports2 packages
- Suggests2 packages