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Augmenting an Artificial Immune Network

Neal, M. and Hunt, J. and Timmis, J. (1998) Augmenting an Artificial Immune Network. In: SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics. IEEE International Conference on Systems, Man, and Cybernetics, 4 . IEEE, pp. 3821-3826. ISBN 0-7803-4778-1. (doi:10.1109/ICSMC.1998.726683) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:21565)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/ICSMC.1998.726683

Abstract

The human immune system can provide many metaphors that can be utilised effectively in the field of machine learning. These metaphors have been successfully applied to the complex real world problem of mortgage fraud detection, using a learning system known as Jisys. The Jisys system identifies patterns in mortgage fraud data by constructing an immune network, which is then evolved through the analysis of additional fraudulent and non-fraudulent applications. By viewing this network, a human expert can gain a better understanding of the fraudulent behavior.

This paper describes significant developments over the original Jisys system. For example, the network is currently a nat structure with significant groupings within it. However, it can be difficult to identify these groups, to analyse them and then determine their significance. This paper describes some advances, which significantly improve the interpretation of the network, We also consider various statistical techniques which can be used to enhance the performance of the Jisys system as well as exploiting inherent properties of the network, which enable significant performance improvements to be implemented (with not loss of information content).

Finally, the paper presents some analysis of the structures generated by the Jisys system and relates them back to the known structures in the training data set.

Item Type: Book section
DOI/Identification number: 10.1109/ICSMC.1998.726683
Uncontrolled keywords: immune system; humans; computer science; loans and mortgages; performance loss; training data; artificial immune systems; machine learning; learning systems
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 21 Aug 2009 23:43 UTC
Last Modified: 16 Nov 2021 09:59 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/21565 (The current URI for this page, for reference purposes)

University of Kent Author Information

Timmis, J..

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