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 expectation-gathering-maximization (EGM) 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.