The FisherEM algorithm, proposed by Bouveyron & Brunet (201) <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.
| Package: | FisherEM |
| Type: | Package |
| Version: | 1.2 |
| Date: | 2012-07-09 |
| License: | GPL-2 |
| LazyLoad: | yes |
Charles Bouveyron, Camille Brunet (2012), "Simultaneous model-based clustering and visualization in the Fisher discriminative subspace.", Statistics and Computing, 22(1), 301-324 <doi:10.1007/s11222-011-9249-9>.
Charles Bouveyron and Camille Brunet (2014), "Discriminative variable selection for clustering with the sparse Fisher-EM algorithm", Computational Statistics, vol. 29(3-4), pp. 489-513 <10.1007/s00180-013-0433-6>.