Paper Abstract and Keywords |
Presentation |
2010-05-14 14:15
A novel method for minimum entropy clustering using competitive learning Toshio Uchiyama, Takeharu Eda, Katsuji Bessho, Tadasu Uchiyama, Katsuyoshi Tanabe (NTT) IE2010-39 PRMU2010-27 MI2010-27 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
We propose a novel method (algorithm), which uses competitive
learning, for clustering based on
minimizing average entropy in clusters (Minimum entropy
criterion). In each iteration, competitive learning usually
decides the winner of models for an input data and then
updates the model of the winner.
When deciding the winner, minimum entropy criterion requires
calculation of the cross-entropy against the models.
However, it is not easy to manage values of stochastic variables in
models with avoiding zero frequency problem, because competitive
learning updates models so many times. Therefore, we present the idea,
which updates models before deciding a winner, to avoid the zero
frequency problem without any bad influence. We also propose a new
method to apply the clustering technique for improving text
classification accuracy. The effectiveness of our methods is shown by
experiments. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Clustering / KL-divergence / Minimum entropy criterion / Competitive learning / Naive Bayes classifier / / / |
Reference Info. |
IEICE Tech. Rep., vol. 110, no. 27, PRMU2010-27, pp. 139-144, May 2010. |
Paper # |
PRMU2010-27 |
Date of Issue |
2010-05-06 (IE, PRMU, MI) |
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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IE2010-39 PRMU2010-27 MI2010-27 |
Conference Information |
Committee |
PRMU IE MI |
Conference Date |
2010-05-13 - 2010-05-14 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Chubu Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2010-05-PRMU-IE-MI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A novel method for minimum entropy clustering using competitive learning |
Sub Title (in English) |
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Keyword(1) |
Clustering |
Keyword(2) |
KL-divergence |
Keyword(3) |
Minimum entropy criterion |
Keyword(4) |
Competitive learning |
Keyword(5) |
Naive Bayes classifier |
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Keyword(7) |
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Keyword(8) |
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1st Author's Name |
Toshio Uchiyama |
1st Author's Affiliation |
NTT CORPORATION (NTT) |
2nd Author's Name |
Takeharu Eda |
2nd Author's Affiliation |
NTT CORPORATION (NTT) |
3rd Author's Name |
Katsuji Bessho |
3rd Author's Affiliation |
NTT CORPORATION (NTT) |
4th Author's Name |
Tadasu Uchiyama |
4th Author's Affiliation |
NTT CORPORATION (NTT) |
5th Author's Name |
Katsuyoshi Tanabe |
5th Author's Affiliation |
NTT CORPORATION (NTT) |
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Speaker |
Author-1 |
Date Time |
2010-05-14 14:15:00 |
Presentation Time |
30 minutes |
Registration for |
PRMU |
Paper # |
IE2010-39, PRMU2010-27, MI2010-27 |
Volume (vol) |
vol.110 |
Number (no) |
no.26(IE), no.27(PRMU), no.28(MI) |
Page |
pp.139-144 |
#Pages |
6 |
Date of Issue |
2010-05-06 (IE, PRMU, MI) |
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