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Data Mining and Statistical Learning

DF21200, 2008HT
Full

Status Archive
School Computer and Information Science (CIS)
Division STIMA
Owner Anders Grimvall
Homepage The course will be coordinated with 732A20 www.ida.liu.se/~732A20

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Course plan

No of lectures

25 x 2h

Recommended for

Doctoral students with a special interest in analysis of large and complex data sets

The course was last given

2007HT

Goals

Prerequisites

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.

Organization

Lectures and computer labs

Contents

Supervised learning (classification and prediction). Model selection. Regression methods. Additive models. Neural networks. Support vector machines.

Literature

Hastie, Tibshirani & Friedman. The elements of statistical learning. Springer.

Lecturers

Anders Grimvall, Oleg Sysoev

Examiner

Anders Grimvall

Examination

Lab reports and final written examination

Credit

12 HEC (Higher Education Credits)

Comments

The course will be coordinated with 732A20
www.ida.liu.se/~732A20


Page responsible: Director of Graduate Studies
Last updated: 2012-05-03