Title: Complexity of magnetic resonance spectrum classification
Authors: Baumgartner, Richard
Ho, Tin Kam
Somorjai, Ray
Himmelreich, Uwe
Sorrell, Tania
Issue Date: 2006
Publisher: Springer Verlag
Host Document: Data Complexity in Pattern recognition, Series: Advanced Information and Knowledge Processing pages:241-248
Abstract: We use several data complexity measures to explain the differences in classification accuracy using various sets of features selected from samples of magnetic resonance
spectra for two-class discrimination. Results suggest that for this typical problem with sparse samples in a high-dimensional space, even robust classifiers like random decision forests can benefit from sophisticated feature selection procedures, and the improvement can be explained
by the more favorable characteristics in the class geometry given by the resultant feature sets.
ISBN: 1-84628-171-7
Publication status: published
KU Leuven publication type: IHb
Appears in Collections:Radiology
Biomedical MRI

Files in This Item:

There are no files associated with this item.

Request a copy


All items in Lirias are protected by copyright, with all rights reserved.