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Paper Abstract and Keywords
Presentation 2007-12-13 11:40
[Special Talk] (not registered)
Shigeo Abe (Kobe Univ.) PRMU2007-139
Abstract (in Japanese) (See Japanese page) 
(in English) Support vector machines (SVM) have been attracting much attention because of their high generalization ability for a wide range of applications. However, because SVMs are originally defined for two-class classification problems, an extension to multiclass problems is not unique and in some extensions unclassifiable regions exist. There are roughly four methods for multiclass problems: (1) one-against-all, (2) pairwise, (3) ECOC (error correcting output code), and (4) all-at-once SVMs. For (1)-(3), unclassifiable regions exist. Another problem is that the SVM is a black box. In this talk, I discuss some approaches to solve these problems fusing SVMs with fuzzy systems. To solve the problem of unclassifiable regions, we propose fuzzy SVMs, in which we introduce membership functions that are orthogonal to the decision functions and define the membership of data for each class. Then I discuss the advantages and disadvantages of these SVMs based on theoretical analysis combined with performance evaluation for some benchmark data sets. As approaches to solve the problem of the black box problem, I talk fuzzy classifiers based on the kernel Mahalanobis distances and kernel discriminant analysis.
Keyword (in Japanese) (See Japanese page) 
(in English) kernel method / kernel Mahalanobis distance / kernel discriminant analysis / support vector machine / multiclass problem / fuzzy system / pattern classification /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 384, PRMU2007-139, pp. 25-25, Dec. 2007.
Paper # PRMU2007-139 
Date of Issue 2007-12-06 (PRMU) 
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 PRMU2007-139

Conference Information
Committee PRMU  
Conference Date 2007-12-13 - 2007-12-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Kobe Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2007-12-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) (not registered) 
Sub Title (in English)  
Keyword(1) kernel method  
Keyword(2) kernel Mahalanobis distance  
Keyword(3) kernel discriminant analysis  
Keyword(4) support vector machine  
Keyword(5) multiclass problem  
Keyword(6) fuzzy system  
Keyword(7) pattern classification  
Keyword(8)  
1st Author's Name Shigeo Abe  
1st Author's Affiliation Kobe University (Kobe Univ.)
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Speaker Author-1 
Date Time 2007-12-13 11:40:00 
Presentation Time 50 minutes 
Registration for PRMU 
Paper # PRMU2007-139 
Volume (vol) vol.107 
Number (no) no.384 
Page p.25 
#Pages 1 
Date of Issue 2007-12-06 (PRMU) 

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