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Paper Abstract and Keywords
Presentation 2015-06-23 14:40
Selective inference for high-order interaction model
Shinya Suzumura, Kazuya Nakagawa (NIT), Koji Tsuda (UT), Ichiro Takeuchi (NIT) IBISML2015-11
Abstract (in Japanese) (See Japanese page) 
(in English) Finding statistically significant high-order interaction features in predictive modeling is important but challenging task. The difficulty lies in the fact that, for a recent applications with high-dimensional covariates, the number of possible high-order interaction features would be extremely large. Identifying statistically significant ones from such a huge pool of candidates would be highly challenging both in computational and statistical senses. In order to work with this problem, we consider a two stage algorithm where we first select a set of high-order interaction features by marginal screening, and then make statistical inferences on the regression model fitted only with the selected features. Using a recently introduced framework called selective-inference, we develop an efficient algorithm for making valid statistical inferences on the post-regression model. The experimental results indicate that the proposed method allows us to reliably identify statistically significant high-order interaction features with reasonable computational cost.
Keyword (in Japanese) (See Japanese page) 
(in English) marginal screening / selection bias / selective inference / high-order interaction / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 112, IBISML2015-11, pp. 69-74, June 2015.
Paper # IBISML2015-11 
Date of Issue 2015-06-16 (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
Conference Date 2015-06-23 - 2015-06-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Institute of Science and Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Machine Learning Approach to Biodata Mining, and General 
Paper Information
Registration To IBISML 
Conference Code 2015-06-NC-BIO-IBISML-MPS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Selective inference for high-order interaction model 
Sub Title (in English)  
Keyword(1) marginal screening  
Keyword(2) selection bias  
Keyword(3) selective inference  
Keyword(4) high-order interaction  
1st Author's Name Shinya Suzumura  
1st Author's Affiliation Nagoya Institute of Technology (NIT)
2nd Author's Name Kazuya Nakagawa  
2nd Author's Affiliation Nagoya Institute of Technology (NIT)
3rd Author's Name Koji Tsuda  
3rd Author's Affiliation The University of Tokyo (UT)
4th Author's Name Ichiro Takeuchi  
4th Author's Affiliation Nagoya Institute of Technology (NIT)
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Speaker Author-1 
Date Time 2015-06-23 14:40:00 
Presentation Time 25 minutes 
Registration for IBISML 
Paper # IBISML2015-11 
Volume (vol) vol.115 
Number (no) no.112 
Page pp.69-74 
Date of Issue 2015-06-16 (IBISML) 

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