Citation

Hejazi, Maryamsadat (2012) Kernel Methods in Anomaly Detection. Masters thesis, Multimedia University.

Full text not available from this repository.

Abstract

The objectives of this research is about evaluation of accuracy and performance of different kernel methods. The results of these methods are demonstrated on credit card fraud dataset to show superiority of one-class SVM (Super Vextor Machine) for anomaly detection problem.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Depositing User:	Users 1102 not found.
Date Deposited:	27 Nov 2012 01:34
Last Modified:	27 Nov 2012 01:34
URII:	http://shdl.mmu.edu.my/id/eprint/3646

Downloads

Edit (login required)