loading...
Training Support Vector Machines Using Gilbert?s Algorithm
Houston, Texas November 27-November 30
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2005.145Fifth IEEE International Conference o ...
 This Article 
 
Buy PURCHASE ARTICLE: $19
PDF
HTML
Buy IEEE Xplore Subscribers
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
ASCII Text
x 
 
Shawn Martin, "Training Support Vector Machines Using Gilbert?s Algorithm," Data Mining, IEEE International Conference on, pp. 306-313, Fifth IEEE International Conference on Data Mining (ICDM'05), 2005.
 
 
BibTex
x
 
@article{ 10.1109/ICDM.2005.145,
author = {Shawn Martin},
title = {Training Support Vector Machines Using Gilbert?s Algorithm},
journal ={Data Mining, IEEE International Conference on},
volume = {0},
year = {2005},
issn = {1550-4786},
pages = {306-313},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2005.145},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Data Mining, IEEE International Conference on
TI - Training Support Vector Machines Using Gilbert?s Algorithm
SN - 1550-4786
SP306
EP313
A1 - Shawn Martin,
PY - 2005
KW - Support Vector Machines
KW - Gilbert?s Algorithm
KW - Nearest Point Algorithm
KW - Sequential Minimal Optimization
VL - 0
JA - Data Mining, IEEE International Conference on
ER -
 
Shawn Martin, Sandia National Laboratories
Support Vector Machines are classifiers designed around the computation of an optimal separating hyperplane. This hyperplane is typically obtained by solving a constrained quadratic programming problem, but may also be located by solving a nearest point problem. Gilbert?s Algorithm can be used to solve this nearest point problem but is unreasonably slow. In this paper we present a modified version of Gilbert?s Algorithm for the fast computation of the Support Vector Machine hyperplane. We then compare our algorithm with the Nearest Point Algorithm and with Sequential Minimal Optimization.
Index Terms:
Support Vector Machines, Gilbert?s Algorithm, Nearest Point Algorithm, Sequential Minimal Optimization
Citation:
Shawn Martin, "Training Support Vector Machines Using Gilbert?s Algorithm," icdm, pp.306-313, Fifth IEEE International Conference on Data Mining (ICDM'05), 2005
Usage of this product signifies your acceptance of the Terms of Use.