Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)

Active Learning Based on diversity maximization

Authors
Yongcheng Wu
Corresponding Author
Yongcheng Wu
Available Online February 2013.
DOI
10.2991/isccca.2013.207How to use a DOI?
Keywords
machine learning, active learning, classification , diversity
Abstract

In many practical data mining applications, unlabeled training examples are readily available but labeled ones are fairly expensive to obtain. Therefore, as one type of the paradigms for addressing the problem of combining labeled and unlabeled data to boost the performance, active learning has attracted much attention. In this paper, we propose a new active learning approach based on diversity maximization. Different from the well-known co-testing algorithm, our method does not require two different views. The comparative studies with other active learning methods demonstrate the effectiveness of the proposed approach.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)
Series
Advances in Intelligent Systems Research
Publication Date
February 2013
ISBN
978-90-78677-63-5
ISSN
1951-6851
DOI
10.2991/isccca.2013.207How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yongcheng Wu
PY  - 2013/02
DA  - 2013/02
TI  - Active Learning Based on diversity maximization
BT  - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)
PB  - Atlantis Press
SP  - 822
EP  - 825
SN  - 1951-6851
UR  - https://doi.org/10.2991/isccca.2013.207
DO  - 10.2991/isccca.2013.207
ID  - Wu2013/02
ER  -