In cognitive science/psychology, Dirichlet process mixture model (DPMM) is considered as a rational model of category learning (Anderson, 1991; Sanborn, Griffiths & Navarro, 2010). That is, the DPMM is used to approximate how human learns to categorise objects.

In this post, I review the DPMM, assuming that all the features are discrete. The implementation in C++ can be found here.