 The fact that the Dirichlet distribution is a probability distribution on the simplex of sets of non-negative numbers that sum to one makes it a good candidate to model distributions over distributions or distributions over functions.Additionally, the nonparametric nature of this model makes it an ideal candidate for clustering problems where the distinct number of clusters is unknown beforehand.In addition, the Dirichlet process has also been used for developing mixture of expert models, in the context of supervised learning algorithms (regression or classification settings).