Paper Abstract and Keywords |
Presentation |
2020-03-17 16:50
Experimental Evaluation for Bayes Error Estimation Capability of Large Geometric Margin Minimum Classification Error Training Ikuhiro Nishiyama (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2019-99 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Previous studies suggested that the Large Geometric Margin-Minimum Classification Error (LGM-MCE) training method had the effect of virtually increasing training samples in a sample space and improving the quality of Bayes error (minimum classification error probability) estimation. However, those studies were simply conducted without sufficiently controlling various estimation-influencing factors. In this paper, we comprehensively control the influencing factors in the LGM-MCE training such as the capability of representing class boundaries (classifiers’ model sizes) and clarify the existence of the effect through experiments using the cross-validation training/testing scheme. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Large geometric margin-minimum classification error training / Virtual sample generation effect / Bayes error estimation / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 481, PRMU2019-99, pp. 231-236, March 2020. |
Paper # |
PRMU2019-99 |
Date of Issue |
2020-03-09 (PRMU) |
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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PRMU2019-99 |
Conference Information |
Committee |
PRMU IPSJ-CVIM |
Conference Date |
2020-03-16 - 2020-03-17 |
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(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2020-03-PRMU-CVIM |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Experimental Evaluation for Bayes Error Estimation Capability of Large Geometric Margin Minimum Classification Error Training |
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Keyword(1) |
Large geometric margin-minimum classification error training |
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Virtual sample generation effect |
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Bayes error estimation |
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1st Author's Name |
Ikuhiro Nishiyama |
1st Author's Affiliation |
Doshisha University (Doshisha Univ.) |
2nd Author's Name |
Hideyuki Watanabe |
2nd Author's Affiliation |
Advanced Telecommunications Research Institute International (ATR) |
3rd Author's Name |
Shigeru Katagiri |
3rd Author's Affiliation |
Doshisha University (Doshisha Univ.) |
4th Author's Name |
Miho Ohsaki |
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Doshisha University (Doshisha Univ.) |
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Speaker |
Author-1 |
Date Time |
2020-03-17 16:50:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2019-99 |
Volume (vol) |
vol.119 |
Number (no) |
no.481 |
Page |
pp.231-236 |
#Pages |
6 |
Date of Issue |
2020-03-09 (PRMU) |