STAT 541 - Statistics for Learning

Course Career Graduate
Units 3
Approved Hours 3-0-0
Fee index 6
Faculty Science
Department Mathematical & Statistical Sci
Typically Offered either term

Description
The course focuses on statistical learning techniques, in particular those of supervised classification, both from statistical (logistic regression, discriminant analysis, nearest neighbours, and others) and “machine learning” background (tree-based methods, neural networks, support vector machines), with the emphasis on decision-theoretic underpinnings and other statistical aspects, flexible model building (regularization with penalties), and algorithmic solutions. Selected methods of unsupervised classification (clustering) and some related regression methods are covered as well. Prerequisite: Consent of the instructor.