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 MPI' implementations such as 'OpenMPI'
See the High Performance Statistical Computing website
for more information, documents and examples.
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