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Paper Abstract and Keywords
Presentation 2015-03-20 14:00
Training of Random Forests Using Covariate Shift on Parallel Distributed Processing
Ryoji Wakayama (Chubu Univ.), Akisato Kimura (NTT), Takayoshi Yamashita, Yuji Yamauchi, Hironobu Fujiyoshi (Chubu Univ.) BioX2014-73 PRMU2014-193
Abstract (in Japanese) (See Japanese page) 
(in English) Machine learning with big data improves a classification performance but increases computatinal cost for learning. Parallel distributed processing on multiple processors GPUs is often used to reduce processing time. This paper exploits MapReduce, an efficient framework for parallel distributed processing and proposes a novel method for training Random Forests by using the MapReduce framework. At the Map job stage, each worker trains a Transfer Forest with shared data to enhance classification performance. At the Reduce job stage, a reducer removes unreliable decision trees constructed at the Map stage, in order to reduce the computational cost of testing. The proposed method can retain the classification performance, even though unbalanced training samples are assigned to each worker.
Keyword (in Japanese) (See Japanese page) 
(in English) Random Forests / Transfer learning / Parallel distributed processing / Machine learning / MapReduce / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 521, PRMU2014-193, pp. 205-210, March 2015.
Paper # PRMU2014-193 
Date of Issue 2015-03-12 (BioX, PRMU) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 PRMU BioX  
Conference Date 2015-03-19 - 2015-03-20 
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 2015-03-PRMU-BioX 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Training of Random Forests Using Covariate Shift on Parallel Distributed Processing 
Sub Title (in English)  
Keyword(1) Random Forests  
Keyword(2) Transfer learning  
Keyword(3) Parallel distributed processing  
Keyword(4) Machine learning  
Keyword(5) MapReduce  
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1st Author's Name Ryoji Wakayama  
1st Author's Affiliation Chubu University (Chubu Univ.)
2nd Author's Name Akisato Kimura  
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
3rd Author's Name Takayoshi Yamashita  
3rd Author's Affiliation Chubu University (Chubu Univ.)
4th Author's Name Yuji Yamauchi  
4th Author's Affiliation Chubu University (Chubu Univ.)
5th Author's Name Hironobu Fujiyoshi  
5th Author's Affiliation Chubu University (Chubu Univ.)
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Speaker Author-1 
Date Time 2015-03-20 14:00:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # BioX2014-73, PRMU2014-193 
Volume (vol) vol.114 
Number (no) no.520(BioX), no.521(PRMU) 
Page pp.205-210 
#Pages
Date of Issue 2015-03-12 (BioX, PRMU) 


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