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An ant colony based system for data mining: applications to medical data

Parpinelli, Rafael S. and Lopes, Heitor S. and Freitas, Alex A. (2001) An ant colony based system for data mining: applications to medical data. In: Spector, Lee E. and Goodman, Erik D., eds. Proceedings of the 3rd Annual Conference on Genetic and Evolutionary Computation. Morgan Kaufmann, San Francisco, California, USA, pp. 791-798. ISBN 1-55860-774-9. (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:13593)

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. (Contact us about this Publication)

Abstract

This work describes an algorithm for rulediscovery in databases called AntMiner. Theobjective of the algorithm is the extraction ofclassification rules to be applied to unseen dataas a decision aid. The algorithm used todiscover such rules is inspired in the behaviorof a real ant colony, as well as some conceptsof information theory and data mining.AntMiner was applied to medical databases toobtain classification rules

Item Type: Book section
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: 24 Nov 2008 17:59 UTC
Last Modified: 16 Feb 2021 12:24 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/13593 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
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