DPmixture
DPmixture refers to a Dirichlet Process mixture model. It is a flexible non-parametric Bayesian model used for clustering and density estimation. Unlike traditional mixture models that require specifying the number of clusters beforehand, DPmixture allows the number of clusters to be inferred from the data. This is achieved by using a Dirichlet Process as a prior for the mixture components. The Dirichlet Process is a probability distribution over distributions, and when used in a mixture model, it encourages sparsity, meaning that many of the mixture components will be effectively empty, leading to a variable number of clusters.
The core idea behind DPmixture is to model data as being generated from a mixture of probability
Applications of DPmixture are broad, ranging from image segmentation and topic modeling to gene expression analysis