Parallel Model-Based Clustering
Description
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.