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

Imbalanced Data Detection Kernel Method in Closed Systems

Authors
Youli Lu, Jun Luo
Corresponding Author
Youli Lu
Available Online May 2014.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
Part of series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
978-94-91216-41-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/iccia.2012.102How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - https://doi.org/10.2991/iccia.2012.102
ID  - Lu2014/05
ER  -