This project is concerned with the implementation of two different Gibbs samplers for a Gaussian Mixture Model (GMM).

Gibbs samplers are clustering algorithms that assume and exploit the distribution assumptions of the clusters (GMM). It thus is more sophisticated than K-mean-clustering algorithm. Gibbs samplers are often used in the text clustering and summary applications.

For detailed implementation, please refer to implementation of Gibbs samplers: a literate programming treatment