Paper Abstract and Keywords |
Presentation |
2018-11-05 15:10
[Poster Presentation]
Compensated Integrated Gradients for Visualization of Features Contributing to EEG Classification Kazuki Tachikawa, Yuji Kawai, Jihoon Park, Minoru Asada (Osaka Univ.) IBISML2018-76 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Integrated gradients method has been widely employed to evaluate the degrees of contribution of input features to classification because it satisfies the desirable axioms for the fair attributions of the contribution.
This method, however, requires an appropriate reference point (hyperparameter) for reliable attributions of the contribution.
We propose compensated integrated gradients method that do not require setting the reference point.
The method compensates the attributions calculated by integrated gradients at an arbitrary reference point using the Shapley sampling value.
We prove that the method can obtain reliable attributions if processes of input features are mutually independent and identical in a classifier.
Using three EEG datasets, we empirically demonstrated that the attributions of the proposed method was more reliable than those of the conventional integrated gradients method, and the computational complexity of the proposed model was much less than that of the Shapley sampling value. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
The Shapley value / Interpretability / EEG / Convolutional Neural Network / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 284, IBISML2018-76, pp. 241-247, Nov. 2018. |
Paper # |
IBISML2018-76 |
Date of Issue |
2018-10-29 (IBISML) |
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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IBISML2018-76 |
Conference Information |
Committee |
IBISML |
Conference Date |
2018-11-05 - 2018-11-07 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hokkaido Citizens Activites Center (Kaderu 2.7) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Information-Based Induction Science Workshop (IBIS2018) |
Paper Information |
Registration To |
IBISML |
Conference Code |
2018-11-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Compensated Integrated Gradients for Visualization of Features Contributing to EEG Classification |
Sub Title (in English) |
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Keyword(1) |
The Shapley value |
Keyword(2) |
Interpretability |
Keyword(3) |
EEG |
Keyword(4) |
Convolutional Neural Network |
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1st Author's Name |
Kazuki Tachikawa |
1st Author's Affiliation |
Osaka Univercity (Osaka Univ.) |
2nd Author's Name |
Yuji Kawai |
2nd Author's Affiliation |
Osaka Univercity (Osaka Univ.) |
3rd Author's Name |
Jihoon Park |
3rd Author's Affiliation |
Osaka Univercity (Osaka Univ.) |
4th Author's Name |
Minoru Asada |
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Osaka Univercity (Osaka Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-11-05 15:10:00 |
Presentation Time |
180 minutes |
Registration for |
IBISML |
Paper # |
IBISML2018-76 |
Volume (vol) |
vol.118 |
Number (no) |
no.284 |
Page |
pp.241-247 |
#Pages |
7 |
Date of Issue |
2018-10-29 (IBISML) |
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