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| Presentation | 2012-11-08 15:00 An Efficient Input Variable Selection for a Linear Regression Model by NC Spectral Clustering Koichi Fujiwara (Kyoto Univ.), Hiroshi Sawada (NTT), Manabu Kano (Kyoto Univ.)  IBISML2012-84 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Linear regression models have been widely accepted in many scientific and engineering fields for the estimation or interpretation of phenomena. When a linear regression model is built, appropriate input variables have to be selected to achieve high estimation performance. This work proposes new methodologies for selecting input variables for linear regression models using nearest correlation spectral clustering (NCSC), which is a correlation-based clustering method. In the present work, NCSC is used for variable group construction, and a few variable groups are selected by their contribution to estimates; it is referred to as NCSC-based variable selection (NCSC-VS). The usefulness of the proposed NCSC-VS is demonstrated through an industrial application to a chemical process. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Linear regression / Variable selection / Spectral clustering / Partial least squares / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 112, no. 279, IBISML2012-84, pp. 359-366, Nov. 2012. | |
| Paper # | IBISML2012-84 | |
| Date of Issue | 2012-10-31 (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) | |
| Download PDF | IBISML2012-84 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2012-11-07 - 2012-11-09 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | the 15th Information-Based Induction Sciences Workshop |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2012-11-IBISML |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An Efficient Input Variable Selection for a Linear Regression Model by NC Spectral Clustering |
| Sub Title (in English) | |
| Keyword(1) | Linear regression |
| Keyword(2) | Variable selection |
| Keyword(3) | Spectral clustering |
| Keyword(4) | Partial least squares |
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| 1st Author's Name | Koichi Fujiwara |
| 1st Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 2nd Author's Name | Hiroshi Sawada |
| 2nd Author's Affiliation | NTT Communication Science Laboratories (NTT) |
| 3rd Author's Name | Manabu Kano |
| 3rd Author's Affiliation | Kyoto University (Kyoto Univ.) |
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| Speaker | Author-1 |
| Date Time | 2012-11-08 15:00:00 |
| Presentation Time | 150 minutes |
| Registration for | IBISML |
| Paper # | IBISML2012-84 |
| Volume (vol) | vol.112 |
| Number (no) | no.279 |
| Page | pp.359-366 |
| #Pages | 8 |
| Date of Issue | 2012-10-31 (IBISML) |
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