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Paper Abstract and Keywords
Presentation 2007-12-22 09:50
Optimizing SVR Hyperparameters via Fast Cross-Validation
Masayuki Karasuyama, Ryohei Nakano (Nagoya Inst. of Tech.) NC2007-73
Abstract (in Japanese) (See Japanese page) 
(in English) The performance of Support Vector Regression (SVR) deeply depends on its hyperparameters such as an insensitive zone thickness, a penalty factor, and kernel parameters. A method called MCV-SVR was once proposed, which optimizes SVR hyperparameters so that cross-validation error is minimized.
However, the computational cost of CV is usually high. In this paper we apply Accurate Online Support Vector Regression (AOSVR) to the MCV-SVR cross-validation procedure. The AOSVR enables an efficient update of a trained SVR function. We show the AOSVR dramatically accelerates the MCV-SVR. Moreover, our experiments showed our faster MCV-SVR has better generalization than other existing methods.
Keyword (in Japanese) (See Japanese page) 
(in English) support vector machines / support vector regression / mimum cross-validation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 410, NC2007-73, pp. 13-18, Dec. 2007.
Paper # NC2007-73 
Date of Issue 2007-12-15 (NC) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NC2007-73

Conference Information
Committee MBE NC  
Conference Date 2007-12-22 - 2007-12-22 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2007-12-MBE-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Optimizing SVR Hyperparameters via Fast Cross-Validation 
Sub Title (in English)  
Keyword(1) support vector machines  
Keyword(2) support vector regression  
Keyword(3) mimum cross-validation  
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1st Author's Name Masayuki Karasuyama  
1st Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
2nd Author's Name Ryohei Nakano  
2nd Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
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Speaker Author-1 
Date Time 2007-12-22 09:50:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2007-73 
Volume (vol) vol.107 
Number (no) no.410 
Page pp.13-18 
#Pages 6 
Date of Issue 2007-12-15 (NC) 

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