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AINE: An Immunological Approach to Data Mining

Knight, Thomas and Timmis, Jon (2001) AINE: An Immunological Approach to Data Mining. In: Cercone, N. and Lin, T. and Wu, Xindon, eds. Proceedings 2001 IEEE International Conference on Data Mining. IEEE, pp. 297-304. ISBN 0-7695-1119-8. (doi:10.1109/ICDM.2001.989532) (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:13518)

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/ICDM.2001.989532

Abstract

An investigation has been undertaken to repeat previous work on an artificial immune system for data analysis called AINE (Artificial Immune Network). The previous work was limited to testing the algorithm on relatively small data sets. The aim of this investigation is two fold, firstly to corroborate the results presented in previous work and secondly, to test the algorithm on a larger and more complex data set. A new re-implementation of AINE is then described and differences in behaviour are identified and explained. It is argued that the behaviour seen in the new implementation is more accurate than that seen in previous work and an in-depth analysis of the algorithm structure is undertaken in order to confirm these observations. The algorithm is also tested on new data and the results of this are presented. Comparisons are draw with other similar techniques for data mining and it is argued that AINE is an effective data-mining algorithm.

Item Type: Book section
DOI/Identification number: 10.1109/ICDM.2001.989532
Uncontrolled keywords: data mining, artificial immune systems, kohonen networks
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
Funders: Institute of Electrical and Electronics Engineers (https://ror.org/01n002310)
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 17:58 UTC
Last Modified: 05 Nov 2024 09:46 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/13518 (The current URI for this page, for reference purposes)

University of Kent Author Information

Timmis, Jon.

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