Prerequisites: STAT 170, STAT 171, STAT 201C; or equivalent; graduate standing
Description: An introduction of mixture models (also known as latent class models or unsupervised learning models). Includes expectation-maximization (EM) algorithm, mixtures of regression models, and their applications such as clustering and density estimation.