The FisherEM package provides an efficient algorithm for the unsupervised classification of high-dimensional data. This FisherEM algorithm models and clusters the data in a discriminative and low-dimensional latent subspace. It also provides a low-dimensional representation of the clustered data.
Charles Bouveyron and Camille Brunet
Maintainer: Camille Brunet <[email protected]>
Charles Bouveyron, Camille Brunet (2012), "Simultaneous model-based clustering and visualization in the Fisher discriminative subspace.", Statistics and Computing, 22(1), 301-324.
Charles Bouveyron, Camille Brunet (2012), "Discriminative variable selection for clustering with the sparse Fisher-EM algorithm", preprint Hal n-00685183.
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