Dirichlet Process Gaussian Mixture Model

Version (6.29 KB) by Mo Chen
Dirichlet Process Gaussian Mixture Model aka Infinite GMM using Gibbs Sampling
Updated 13 Mar 2016

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This package solves the Dirichlet Process Gaussian Mixture Model (aka Infinite GMM) with Gibbs sampling. This is nonparametric Bayesian treatment for mixture model problems which automatically selects the proper number of the clusters.
I includes the Gaussian component distribution in the package. However, the code is flexible enough for Dirichlet process mixture model of any distribution. User can write your own class for the base distribution then let the underlying Gibbs sampling engine do the inference work.
Please try the demo script in the package.

This package is now a part of the PRML toolbox (http://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox).

Cite As

Mo Chen (2024). Dirichlet Process Gaussian Mixture Model (https://www.mathworks.com/matlabcentral/fileexchange/55865-dirichlet-process-gaussian-mixture-model), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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