de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Fast Pattern Selection Algorithm for Support Vector Classifiers: "Time Complexity Analysis"

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84217

Shin,  H
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

Locator
There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Shin, H. (2003). Fast Pattern Selection Algorithm for Support Vector Classifiers: "Time Complexity Analysis". In The 4th International Conference on Intelligent Data Engineering (IDEAL) (pp. 1008-1015). Heidelberg: Springer-Verlag.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-DBB3-9
Abstract
Training SVM requires large memory and long cpu time when the pattern set is large. To alleviate the computational burden in SVM training, we propose a fast preprocessing algorithm which selects only the patterns near the decision boundary. The time complexity of the proposed algorithm is much smaller than that of the naive M^2 algorithm