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[Lunds Universitet]

Elements of Statistical Learning, 5p (7.5 ETCS credits)


Study circle, spring 2008

News

Course Coordinator

Erik Lindström, tel 046-222 45 78, , MH:129.

General information

University credits: 7.5

Lectures:

Lecturer Day Chapter Exercises
Erik Lindström 14/1 M 1 Introduction
2 Overview of Superv. Learning
2.2, 2.6
Martin Byröd 21/1 M 3 Lin. meth. for regression 3.3, 3.11
Susann Stjernqvist 24/1 T 4 Lin. meth. for classification 4.2 a-c, 4.5
David Bolin 28/1 M 5 Basis expansion and regularization 5.1, 5.7
Jakob Sternby 31/1 T 6 Kernel methods 6.3, 6.8
Mats Brodén 4/2 M 7 Model assessment and selection 7.1, 7.4
Jonas Ströjby 7/2 T 8 Model Inference and averaging 8.2, 8.4
Johan Sandberg 11/2 M 9 Additive models and trees 9.1, 9.3 or 9.7b
Johannes Sivén 18/2 M 10 Boosting and additive trees 10.5
Johan Lindström 25/2 M 13 Prototype methods 13.1, 13.7
Charlotte Soneson 3/3 M 12 Support Vector Machines 12.1, 12.10
Jörg Wegener 10/3 M 11 Neural networks 11.1, 11.2
Olof Enqvist 17/3 M 14 Unsupervised learning 14.3, valfri
List of activities can be found here.

Literature

The Elements of Statistical Learning, Hastie, Tibshirani and Friedman (2001). Springer-Verlag. 536 pages, see also the book homepage

Assessment

Active participation in the course as discussed during the course.
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