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| Presentation | 2011-01-25 11:15 Learning from Partially Supervised Data Stream Using Past Instances To Label Clusters Tatsuya Kosaka (Kobe Univ.), Yoshiaki Yasumura (Shibaura It.), Kuniaki Uehara (Kobe Univ.)  KBSE2010-41 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This report presents a learning method for a partially supervised data stream that contains few labeled positive and unlabeled data. Instances in a data stream are divided into chunks, which contains a fixed size of instances. This method is based on the ensemble approach that builds classifiers from chunks. Then, in order to learn from a chunk, this method extracts reliable negative instances from unlabeled data using k-means clustering with labeled positives in the past chunks. To detect concept change in a data stream, clusters are assigned the weights based on the distance between the clusters containing labeled positives in the coming chunk and the clusters containing it in the past ones. The experiment results using an artificial data stream show the validity of the proposed method. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | data stream / partially supervised learning / concept change / K-means clustering / past instances / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 110, no. 386, KBSE2010-41, pp. 37-42, Jan. 2011. | |
| Paper # | KBSE2010-41 | |
| Date of Issue | 2011-01-17 (KBSE) | |
| 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 | KBSE2010-41 |
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| Conference Information | |
| Committee | KBSE |
| Conference Date | 2011-01-24 - 2011-01-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kikai-Shinko-Kaikan Bldg. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Knowledge-Based Software Engineering, etc. |
| Paper Information | |
| Registration To | KBSE |
| Conference Code | 2011-01-KBSE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Learning from Partially Supervised Data Stream Using Past Instances To Label Clusters |
| Sub Title (in English) | |
| Keyword(1) | data stream |
| Keyword(2) | partially supervised learning |
| Keyword(3) | concept change |
| Keyword(4) | K-means clustering |
| Keyword(5) | past instances |
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| Keyword(8) | |
| 1st Author's Name | Tatsuya Kosaka |
| 1st Author's Affiliation | Kobe University (Kobe Univ.) |
| 2nd Author's Name | Yoshiaki Yasumura |
| 2nd Author's Affiliation | Shibaura Institute of Technology (Shibaura It.) |
| 3rd Author's Name | Kuniaki Uehara |
| 3rd Author's Affiliation | Kobe University (Kobe Univ.) |
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| Speaker | Author-1 |
| Date Time | 2011-01-25 11:15:00 |
| Presentation Time | 45 minutes |
| Registration for | KBSE |
| Paper # | KBSE2010-41 |
| Volume (vol) | vol.110 |
| Number (no) | no.386 |
| Page | pp.37-42 |
| #Pages | 6 |
| Date of Issue | 2011-01-17 (KBSE) |
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