Paper Abstract and Keywords |
Presentation |
2013-03-05 11:25
Elimination of redundant features by Kernel Methods and Random Matrix Theory Hideko Kawakubo, Hiroaki Yoshida (Ochanomizu Univ) IBISML2012-102 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Feature selection can be used to detect factors that affect a certain phenomenon. If the subset of the selected factors is exact and the minimum, the cost concerning investigation can be reduced when we investigate about the selected factors. However, since only a local optimal solution can be obtained by existing feature selection methods, the number of features to select needs to be determined artificially.
In this study, we will propose a method of extracting the minimum subset of useful features automatically without such an artificial determination, and demonstrate the effectiveness of our method. Combining Hilbert Schmidt Independence Criterion and Random Matrix Theory, elimination of redundant features can be performed.
In addition, this study would give an index about the parameter optimization of Hilbert Schmidt Independence Criterion. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Hilbert Schmidt Independence Criterion / Random Matrix Theory / feature selection / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 454, IBISML2012-102, pp. 69-76, March 2013. |
Paper # |
IBISML2012-102 |
Date of Issue |
2013-02-25 (IBISML) |
ISSN |
Print edition: ISSN 0913-5685 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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IBISML2012-102 |
Conference Information |
Committee |
IBISML |
Conference Date |
2013-03-04 - 2013-03-05 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Nagoya Institute of Technology |
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(See Japanese page) |
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Paper Information |
Registration To |
IBISML |
Conference Code |
2013-03-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Elimination of redundant features by Kernel Methods and Random Matrix Theory |
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Hilbert Schmidt Independence Criterion |
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Random Matrix Theory |
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feature selection |
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1st Author's Name |
Hideko Kawakubo |
1st Author's Affiliation |
Ochanomizu University (Ochanomizu Univ) |
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Hiroaki Yoshida |
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Ochanomizu University (Ochanomizu Univ) |
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Speaker |
Author-1 |
Date Time |
2013-03-05 11:25:00 |
Presentation Time |
25 minutes |
Registration for |
IBISML |
Paper # |
IBISML2012-102 |
Volume (vol) |
vol.112 |
Number (no) |
no.454 |
Page |
pp.69-76 |
#Pages |
8 |
Date of Issue |
2013-02-25 (IBISML) |
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