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pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model
Version 0.2-0
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 MPI' implementations such as 'OpenMPI'
and 'MPICH'.
See the High Performance Statistical Computing website
Getting started
Browse package contents
Package details |
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|---|---|
| Author | Wei-Chen Chen [aut, cre], George Ostrouchov [aut] |
| Date of publication | 2018-02-02 04:41:01 UTC |
| Maintainer | Wei-Chen Chen <[email protected]> |
| License | GPL (>= 2) |
| Version | 0.2-0 |
| URL | http://r-pbd.org/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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