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pmclust (version 0.1-7)

Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

Description

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 expectation-gathering-maximization 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 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 and examples.

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Install

install.packages('pmclust')

Monthly Downloads

200

Version

0.1-7

License

GPL (>= 2)

Maintainer

Last Published

January 25th, 2016

Functions in pmclust (0.1-7)