Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)

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Imbalanced Data Detection Kernel Method in Closed Systems

Authors
Youli Lu, Jun Luo
Corresponding Author
Youli Lu
Available Online May 2014.
DOI
10.2991/iccia.2012.102How to use a DOI?
Keywords
component, Kernel Method, SVDD, Imbalaced Classification,
Abstract

Under the study of Kernel Methods, this paper put forward two improved algorithm which called R-SVM & I-SVDD in order to cope with the imbalanced data sets in closed systems. R-SVM used K-means algorithm clustering space samples while I-SVDD improved the performance of original SVDD by imbalanced sample training. Experiment of two sets of system call data set shows that these two algorithms are more effectively and R-SVM has a lower complexity.

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 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
Series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
10.2991/iccia.2012.102
ISSN
1951-6851
DOI
10.2991/iccia.2012.102How 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

risenwbib
TY  - CONF
AU  - Youli Lu
AU  - Jun Luo
PY  - 2014/05
DA  - 2014/05
TI  - Imbalanced Data Detection Kernel Method in Closed Systems
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 423
EP  - 428
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.102
DO  - 10.2991/iccia.2012.102
ID  - Lu2014/05
ER  -