Introduction to statistical pattern recognition. The main topics include Bayes decision theory, discriminant functions, maximum likelihood estimation, PCA, LDA, semi-supervised kernel learning, and graph embedding. This course will discuss some applications of data mining in different application fields, such as business, marketing, medical imaging, biology. Prerequisite: MATH 3330.