Data Mining and Statistical LearningDF21200, 2008HT
No of lectures
25 x 2h
Doctoral students with a special interest in analysis of large and complex data sets
The course was last given
Undergraduate studies with a minimum of 90 ECTS credits in mathematics, statistics and computer science together and at least one course in each of the following topics: linear algebra, statistical inference and computer science.
Lectures and computer labs
Supervised learning (classification and prediction). Model selection. Regression methods. Additive models. Neural networks. Support vector machines.
Hastie, Tibshirani & Friedman. The elements of statistical learning. Springer.
Anders Grimvall, Oleg Sysoev
Lab reports and final written examination
12 HEC (Higher Education Credits)
The course will be coordinated with 732A20
Page responsible: Director of Graduate Studies
Last updated: 2012-05-03