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Paper Abstract and Keywords
Presentation 2014-01-23 11:00
Large Geometric Margin Minimum Classification Error Training with Automatic Optimization Of The Number of Prototypes
Yuji Takayama (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-94 MVE2013-35
Abstract (in Japanese) (See Japanese page) 
(in English) Large Geometric Margin Minimum Classification Error (LGM-MCE) training, which adopts geometric-margin-based misclassification measure, was successfully applied to the training of multi-prototype classifiers, of
which discriminant function is the geometric distance between an input pattern and multiple prototypes. However, a rational method for setting the number of prototypes has not yet been developed. To alleviate this problem, we propose in this paper a new method for appropriately setting the number of prototypes based on classification accuracies observed in the course of LGM-MCE training. Experiment results clearly demonstrate the high utility
of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Minimum classification error / Geometric margin / Number of prototypes / / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 402, PRMU2013-94, pp. 19-24, Jan. 2014.
Paper # PRMU2013-94 
Date of Issue 2014-01-16 (PRMU, MVE) 
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 PRMU2013-94 MVE2013-35

Conference Information
Committee PRMU IPSJ-CVIM MVE  
Conference Date 2014-01-23 - 2014-01-24 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2014-01-PRMU-CVIM-MVE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Large Geometric Margin Minimum Classification Error Training with Automatic Optimization Of The Number of Prototypes 
Sub Title (in English)  
Keyword(1) Minimum classification error  
Keyword(2) Geometric margin  
Keyword(3) Number of prototypes  
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1st Author's Name Yuji Takayama  
1st Author's Affiliation Doshisiha University (Doshisha Univ.)
2nd Author's Name Hideyuki Watanabe  
2nd Author's Affiliation National Institute of Information and Communications Technology (NICT)
3rd Author's Name Shigeru Katagiri  
3rd Author's Affiliation Doshisiha University (Doshisha Univ.)
4th Author's Name Miho Ohsaki  
4th Author's Affiliation Doshisiha University (Doshisha Univ.)
5th Author's Name Shigeki Matsuda  
5th Author's Affiliation National Institute of Information and Communications Technology (NICT)
6th Author's Name Chiori Hori  
6th Author's Affiliation National Institute of Information and Communications Technology (NICT)
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Speaker Author-1 
Date Time 2014-01-23 11:00:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2013-94, MVE2013-35 
Volume (vol) vol.113 
Number (no) no.402(PRMU), no.403(MVE) 
Page pp.19-24 
#Pages 6 
Date of Issue 2014-01-16 (PRMU, MVE) 

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