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Paper Abstract and Keywords
Presentation 2018-03-06 10:00
Learning rule-base model by Safe Pattern Pruning
Hiroki Kato, Hiroyuki Hanada (Nagoya Inst. of Tech.), Ichiro Takeuchi (Nagoya Inst. of Tech./RIKEN/NIMS) IBISML2017-98
Abstract (in Japanese) (See Japanese page) 
(in English) We consider learning the prediction model called ''rule-base model''. Rule-base model is the model which uses ''rules'' as explanatory variables. Here a ''rule'' must be described as, for example, ''one's age is 20-29 years old and his/her weight is 70-80kg''. Because the number of rules that can be created from the training data set is enormous by its combinatorial nature, it is difficult to learn the model by using all of them. In this study, we propose a method which can learn rule-base models by converting the learning to the predictive pattern mining problem and using the method called Safe Pattern Pruning (SPP). Furthermore, we confirm its usefulness through numerical experiments.
Keyword (in Japanese) (See Japanese page) 
(in English) Rule-base model / Sparse learning / Safe screening / Safe pattern pruning / Empirical risk minimization / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 475, IBISML2017-98, pp. 55-62, March 2018.
Paper # IBISML2017-98 
Date of Issue 2018-02-26 (IBISML) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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 2018-03-05 - 2018-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Nishijin Plaza, Kyushu University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Statisitical Mathematics, Machine Learning, Data Mining, etc. 
Paper Information
Registration To IBISML 
Conference Code 2018-03-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Learning rule-base model by Safe Pattern Pruning 
Sub Title (in English)  
Keyword(1) Rule-base model  
Keyword(2) Sparse learning  
Keyword(3) Safe screening  
Keyword(4) Safe pattern pruning  
Keyword(5) Empirical risk minimization  
1st Author's Name Hiroki Kato  
1st Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
2nd Author's Name Hiroyuki Hanada  
2nd Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
3rd Author's Name Ichiro Takeuchi  
3rd Author's Affiliation Nagoya Institute of Technology/RIKEN/National Institute for Materials Science (Nagoya Inst. of Tech./RIKEN/NIMS)
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Speaker Author-2 
Date Time 2018-03-06 10:00:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # IBISML2017-98 
Volume (vol) vol.117 
Number (no) no.475 
Page pp.55-62 
Date of Issue 2018-02-26 (IBISML) 

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