ASRM 551. Statistical Learning (Same as STAT 542)
Modern techniques of predictive modeling, classification, and clustering are discussed. Examples of these are linear regression, nonparametric regression, kernel methods, regularization, cluster analysis, classification trees, neural networks, boosting, discrimination, support vector machines, and model selection. Applications are discussed as well as computation and theory.
4 graduate hours. No professional credit. Prerequisite: STAT 410 and STAT 425.