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).
引用格式
Mo Chen (2024). Dirichlet Process Gaussian Mixture Model (https://www.mathworks.com/matlabcentral/fileexchange/55865-dirichlet-process-gaussian-mixture-model), MATLAB Central File Exchange. 检索时间: .
MATLAB 版本兼容性
平台兼容性
Windows macOS Linux类别
标签
致谢
参考作品: EM Algorithm for Gaussian Mixture Model (EM GMM), Variational Bayesian Inference for Gaussian Mixture Model, Pattern Recognition and Machine Learning Toolbox
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!DP/
版本 | 已发布 | 发行说明 | |
---|---|---|---|
1.0.0.0 | update description |