STAT 542

Fall 2014 All Classes

All Classes

Statistical Learning

Credit: 4 hours.

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.

Prerequisite: STAT 410 and STAT 425.

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STAT 542 class schedule data for fall 2014
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	50222	Lecture	L1	2:00PM -3:20PM	TR	319 Gregory Hall	Liang, F	Part of Term: 1 Date Range: 08/25/14-12/10/14 Section Info: Restricted to Statistics Graduate Students until May 5, 2014. Some seats are reserved for incoming Statistics graduate students. If you receive a Reserved-Closed error, that means the course is full except for the reserved seats. Restriction(s): Restricted to Graduate - Urbana-Champaign.