Paper Abstract and Keywords |
Presentation |
2018-03-05 13:50
Metric Learning for k-Nearest Neighbor Estimation using Multiple Distance Metrics Yokuto Seki, Noboru Murata (Waseda Univ.) IBISML2017-92 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The relationship between unstructured datasets such as graphs can be measured by multiple distance metrics.
In this paper, we propose a new metric learning method for $k$-nearest neighbor using multiple distance metrics.
In our proposed method, the neighborhood relations with respect to the target distance metric are estimated from the neighborhood relations with respect to other multiple distance metrics.
We use decision tree to direct sum decompose datasets to small datasets which holds the neighborhood relations with respect to the target distance metric.
Following Random Forest, we use bootstrap sampling and sample distance to decompose datasets in various manners.
The proximity among the datasets are calculated from the decomposition result.
We conducted numerical experiments with an artificial datasets, and a real datasets concerning floor plan. The experiments show the improvement of accuracy. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Metric Learning / k-Nearest Neighbor Estimation / Decision Tree / Unstructured Data / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 475, IBISML2017-92, pp. 15-19, March 2018. |
Paper # |
IBISML2017-92 |
Date of Issue |
2018-02-26 (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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IBISML2017-92 |
Conference Information |
Committee |
IBISML |
Conference Date |
2018-03-05 - 2018-03-06 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Nishijin Plaza, Kyushu University |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Statisitical Mathematics, Machine Learning, Data Mining, etc. |
Paper Information |
Registration To |
IBISML |
Conference Code |
2018-03-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Metric Learning for k-Nearest Neighbor Estimation using Multiple Distance Metrics |
Sub Title (in English) |
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Keyword(1) |
Metric Learning |
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k-Nearest Neighbor Estimation |
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Decision Tree |
Keyword(4) |
Unstructured Data |
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1st Author's Name |
Yokuto Seki |
1st Author's Affiliation |
Waseda University (Waseda Univ.) |
2nd Author's Name |
Noboru Murata |
2nd Author's Affiliation |
Waseda University (Waseda Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-03-05 13:50:00 |
Presentation Time |
25 minutes |
Registration for |
IBISML |
Paper # |
IBISML2017-92 |
Volume (vol) |
vol.117 |
Number (no) |
no.475 |
Page |
pp.15-19 |
#Pages |
5 |
Date of Issue |
2018-02-26 (IBISML) |
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