[an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] /Opinnot/T-61.6040/project_s06/www/project.html [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive]
Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology


T-61.6040 Special Course in Computer and Information Science IV L:

Variable Selection for Regression



Computer Assignment

The computer assignment consists of implementing one method for input selection. The methods are tested on the test problems given in this page. The topics of the assignments are decided individually. For questions please contact the course assistant.

Reporting

Reporting is done using the given latex or word template. Deadline for returning the reports is 22.12. The report can be returned by email in PDF format. The students should report the relevant results and also the method they implemented in a general level. Each student tests one method.

Templates

The templates are from the ESTSP conference which will be organized next year.

Code

Currently public matlab code related to the project is available here. The final goal is to have a matlab toolbox with a graphical interface.

Test Problems

The test problems are available here. See also the slides of the first lecture. The electricity consumption time series should be divided into windows of length 20 to generate the inputs. Generate the scalar output corresponding to direct 10 step ahead prediction. On the boston housing data choose 380 data randomly from the whole set for training and use the rest to calculate the test error. It is a good idea to normalize data before input selection and regression!

You are at: CIS → /Opinnot/T-61.6040/project_s06/www/project.html

Page maintained by webmaster at cis.hut.fi, last updated Saturday, 25-Nov-2006 16:38:53 EET

[an error occurred while processing this directive]
Google
WWW www.cis.hut.fi