FisherEM

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

CRAN Package

The FisherEM algorithm, proposed by Bouveyron & Brunet (2012) , 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.

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  • Depends4 packages
  • Imports2 packages
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