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Paper Abstract and Keywords
Presentation 2013-03-05 15:40
Hierarchical Multi-label Classification on Statistical Decision Theory
Kiyohito Yamamoto, Tota Suko, Toshiyasu Matsushima (Waseda Univ.) IBISML2012-107
Abstract (in Japanese) (See Japanese page) 
(in English) This paper considers multi-label classification on statistical decision theory. In Label Power Set format, multi-label classification is equivalent to multi-class classification. However, the number of classes increases exponentially as elements in label set grow in number. Hence in case of many labels, a prohibitive computational cost problem occurs. To avoid this problem, some studies have been done and one of them used hierarchical structure. On the other hand, optimal classification method based on bayes rule has been attracted much attention recently. We apply this optimal classification method based on bayes rule to multi-label classification problem. Moreover, assuming hierarchical structure on labels, we propose efficient classification algorithms which reduce computational cost to linear order on the number of elements in label set. Since optimal classification based on bayes rule differs calculation formula depending loss function, we present algorithms in case of 0-1 loss and hamming loss, respectively.
Keyword (in Japanese) (See Japanese page) 
(in English) multi-label classification / statistical decision theory / hierarchical structure / algorithm / / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 454, IBISML2012-107, pp. 101-106, March 2013.
Paper # IBISML2012-107 
Date of Issue 2013-02-25 (IBISML) 
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)
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Conference Information
Committee IBISML  
Conference Date 2013-03-04 - 2013-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Nagoya Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IBISML 
Conference Code 2013-03-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Hierarchical Multi-label Classification on Statistical Decision Theory 
Sub Title (in English)  
Keyword(1) multi-label classification  
Keyword(2) statistical decision theory  
Keyword(3) hierarchical structure  
Keyword(4) algorithm  
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1st Author's Name Kiyohito Yamamoto  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Tota Suko  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Toshiyasu Matsushima  
3rd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2013-03-05 15:40:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # IBISML2012-107 
Volume (vol) vol.112 
Number (no) no.454 
Page pp.101-106 
#Pages 6 
Date of Issue 2013-02-25 (IBISML) 

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