Imbalanced Data Detection Kernel Method in Closed Systems

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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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  -