/STA 567. Statistical Learning

Catalog description

Introduction to methods of statistical learning, with emphases on both theory and implementation. Topics include supervised and unsupervised learning methods, including linear and nonlinear models for regression and classification, additive models, recursive partitioning methods, neural networks, support vector machines, association rules, and cluster analysis; ensemble methods; and methods of model assessment and selection. Credit not awarded for both STA 467/STA 567 and ISA 491/ISA 591 . Prerequisite: STA 463/STA 563 with a grade of C or better.