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Paper Abstract and Keywords
Presentation 2020-12-02 10:30
Error Probability of Classification Based on the Analysis of the Bayes Code -- Extension and Example --
Shota Saito, Toshiyasu Matsushima (Waseda Univ.) IT2020-32
Abstract (in Japanese) (See Japanese page) 
(in English) Suppose that we have two training sequences generated by parametrized distributions $P_{theta^*}$ and $P_{xi^*}$, where $theta^*$ and $xi^*$ are unknown true parameters. Given training sequences, we study the problem of classifying whether a test sequence was generated according to $P_{theta^*}$ or $P_{xi^*}$. This problem can be thought of as a hypothesis testing problem and our aim is to analyze the weighted sum of type-I and type-II error probabilities. Utilizing the analysis of the codeword lengths of the Bayes code, our previous study derived more refined bounds on the error probability than known previously. However, our previous study had the following deficiencies: i) the prior distributions of $theta$ and $xi$ are the same; ii) the prior distributions of two hypotheses are uniform; iii) the tightness of the upper and lower bounds were not clear. This study solves these problems. We remove the restrictions i) and ii) and derive more general results than obtained previously. To deal with the problem iii), we perform numerical calculation for a concrete model.
Keyword (in Japanese) (See Japanese page) 
(in English) Bayes code / Chernoff information / hypothesis testing / statistical classification problem / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 268, IT2020-32, pp. 44-49, Dec. 2020.
Paper # IT2020-32 
Date of Issue 2020-11-24 (IT) 
ISSN Online edition: ISSN 2432-6380
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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 IT  
Conference Date 2020-12-01 - 2020-12-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Lectures for Young Researchers, General 
Paper Information
Registration To IT 
Conference Code 2020-12-IT 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Error Probability of Classification Based on the Analysis of the Bayes Code 
Sub Title (in English) Extension and Example 
Keyword(1) Bayes code  
Keyword(2) Chernoff information  
Keyword(3) hypothesis testing  
Keyword(4) statistical classification problem  
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1st Author's Name Shota Saito  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Toshiyasu Matsushima  
2nd Author's Affiliation Waseda University (Waseda Univ.)
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Date Time 2020-12-02 10:30:00 
Presentation Time 20 minutes 
Registration for IT 
Paper # IT2020-32 
Volume (vol) vol.120 
Number (no) no.268 
Page pp.44-49 
#Pages
Date of Issue 2020-11-24 (IT) 


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