pmclust: Parallel Model-Based Clustering

The pmclust aims to utilize model-based clustering (unsupervised) for high dimensional and ultra large data, especially in a distributed manner. The package employs Rmpi to perform a parallel version of expectation and maximization (EM) algorithm 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 (SPMD) programming model. The code can be executed through Rmpi and independent to most MPI applications. See the High Performance Statistical Computing (HPSC) website for more information, documents and examples.

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