DocumentCode :
2896973
Title :
A Modified Value Difference Metric Kernel for Context-Dependent Classification Tasks
Author :
Liu, Feng ; Vanschoenwinkel, Bram ; Chen, Yi-fei ; Manderick, Bernard
Author_Institution :
Dept. of Informatics, Vrije Univ., Brussels
fYear :
2006
fDate :
13-16 Aug. 2006
Firstpage :
3432
Lastpage :
3437
Abstract :
This paper focuses on the use of support vector machines on context-dependent classification tasks, like gene splice site prediction. For this type of problems, it has been shown that a context-based approach should be preferred over a transformation approach as this is a much more intuitive setting for working with distance functions. A weighted overlap metric and a modified value difference metric are described and subsequently used in several context-sensitive kernel functions. As a case-study gene splice site prediction is used and the experimental results show that the context-sensitive kernels making use of different weights and the modified value difference metric can always outperform their simple non-sensitive counterparts both in accuracy and in model complexity
Keywords :
biology computing; genetics; pattern classification; support vector machines; context-dependent classification task; context-sensitive kernel function; gene splice site prediction; support vector machine; weighted overlap metric; Computational modeling; Context modeling; Cybernetics; DNA; Electronic mail; Informatics; Kernel; Machine learning; Proteins; Sequences; Support vector machine classification; Support vector machines; Gene Splice Site Prediction; Kernel Functions; Modified Value Difference Metric; Support Vector Machines; Weighted Overlap Metric;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
Type :
conf
DOI :
10.1109/ICMLC.2006.258509
Filename :
4028663
Link To Document :
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