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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.6 |
rolling source/ R- | FisherEM_1.6.tar.gz |
105.9 KiB |
1.6 |
latest source/ R- | FisherEM_1.6.tar.gz |
105.9 KiB |
1.6 |
2026-04-23 source/ R- | FisherEM_1.6.tar.gz |
105.9 KiB |
1.6 |
2026-04-09 windows/windows R-4.5 | FisherEM_1.6.zip |
223.3 KiB |