pmclust: Parallel Model-Based Clustering using
Expectation-Gathering-Maximization Algorithm for Finite Mixture
Aims to utilize model-based clustering (unsupervised)
for high dimensional and ultra large data, especially in a distributed
manner. The code employs pbdMPI to perform a
for finite mixture Gaussian
models. The unstructured dispersion matrices are assumed in the
Gaussian models. The implementation is default in the single program
multiple data programming model. The code can be executed
through pbdMPI and independent to most MPI applications.
See the High Performance
Statistical Computing website for more information, documents
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