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Paper Abstract and Keywords
Presentation 2022-06-25 10:05
Time Series Analysis of Shapley Values in Machine-Learning Regression
Kotaro Kuno, Yukari Shirota (GakushuinUniv) DE2022-1
Abstract (in Japanese) (See Japanese page) 
(in English) In regression analysis of machine learning, Lundberg's SHAP and its libraries are widely used and have contributed greatly to the semantic interpretation of regression analysis across various application fields. In this paper, we introduce an approach to apply SHAP to time series analysis.
The advantage of SHAP is that it can evaluate the contribution of each explanatory variable to the target variable value, using the characteristic function of each data. If the target value are time series data, even if the same explanatory variable dataset is used, the SHAP values obtained from the regressions become different. By analyzing the time series changes, it is possible to extract the most important explanatory variables at that time. In this paper, we show the evaluation of explanatory variables based on the characteristics of each company by SHAP, using a case study of the stock price recovery rate after the stock price decline by the COVID-19 in global automobile manufacturing industries.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Regression / Shapley values / SHAP / Time series analysis of SHAP distribution / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 88, DE2022-1, pp. 1-6, June 2022.
Paper # DE2022-1 
Date of Issue 2022-06-17 (DE) 
ISSN 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 DE  
Conference Date 2022-06-24 - 2022-06-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Musashino University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Social Computing 
Paper Information
Registration To DE 
Conference Code 2022-06-DE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Time Series Analysis of Shapley Values in Machine-Learning Regression 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Regression  
Keyword(3) Shapley values  
Keyword(4) SHAP  
Keyword(5) Time series analysis of SHAP distribution  
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1st Author's Name Kotaro Kuno  
1st Author's Affiliation Gakushuin University (GakushuinUniv)
2nd Author's Name Yukari Shirota  
2nd Author's Affiliation Gakushuin University (GakushuinUniv)
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Speaker Author-1 
Date Time 2022-06-25 10:05:00 
Presentation Time 20 minutes 
Registration for DE 
Paper # DE2022-1 
Volume (vol) vol.122 
Number (no) no.88 
Page pp.1-6 
#Pages
Date of Issue 2022-06-17 (DE) 


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