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Paper Abstract and Keywords
Presentation 2012-10-19 15:55
Variable Selection Method in Multiple Regression with Incomplete Sensor Data
Hisashi Kurasawa, Hiroshi Sato, Atsushi Yamamoto, Hitoshi Kawasaki, Motonori Nakamura, Hajime Matsumura (NTT) USN2012-54
Abstract (in Japanese) (See Japanese page) 
(in English) Participatory sensing brings incomplete sensor data due to the spatio-temporal uncertainty of the observation. We have to make up for the missing values in the sensor data for applications. We proposed a variable selection method in multiple regression. It accurately predicts the missing values by repeating two steps; firstly selecting high correlated variables, and then updating the complete sensor data including the selected variables for the regression. Empirical evaluations show that our method increases the complete sensor data and improves the prediction accuracy by repeated variable selections.
Keyword (in Japanese) (See Japanese page) 
(in English) Participatory sensing / Missing data / Variable Selection / / / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 242, USN2012-54, pp. 149-154, Oct. 2012.
Paper # USN2012-54 
Date of Issue 2012-10-10 (USN) 
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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee SR AN USN RCS  
Conference Date 2012-10-17 - 2012-10-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukuoka univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) wireless distributed network, general topics 
Paper Information
Registration To USN 
Conference Code 2012-10-SR-AN-USN-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Variable Selection Method in Multiple Regression with Incomplete Sensor Data 
Sub Title (in English)  
Keyword(1) Participatory sensing  
Keyword(2) Missing data  
Keyword(3) Variable Selection  
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1st Author's Name Hisashi Kurasawa  
1st Author's Affiliation NTT Network Innovation Laboratories, NTT Corporation (NTT)
2nd Author's Name Hiroshi Sato  
2nd Author's Affiliation NTT Network Innovation Laboratories, NTT Corporation (NTT)
3rd Author's Name Atsushi Yamamoto  
3rd Author's Affiliation NTT Network Innovation Laboratories, NTT Corporation (NTT)
4th Author's Name Hitoshi Kawasaki  
4th Author's Affiliation NTT Network Innovation Laboratories, NTT Corporation (NTT)
5th Author's Name Motonori Nakamura  
5th Author's Affiliation NTT Network Innovation Laboratories, NTT Corporation (NTT)
6th Author's Name Hajime Matsumura  
6th Author's Affiliation NTT Network Innovation Laboratories, NTT Corporation (NTT)
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Speaker
Date Time 2012-10-19 15:55:00 
Presentation Time 25 
Registration for USN 
Paper # IEICE-USN2012-54 
Volume (vol) IEICE-112 
Number (no) no.242 
Page pp.149-154 
#Pages IEICE-6 
Date of Issue IEICE-USN-2012-10-10 


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