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An Ant Colony Algorithm for Classification Rule Discovery

Parpinelli, Rafael S. and Lopes, Heitor S. and Freitas, Alex A. (2002) An Ant Colony Algorithm for Classification Rule Discovery. In: Abbass, Hussein Aly and Sarker, Ruhul Amin and Newton, Charles S., eds. Data Mining: a Heurstic Approach. Idea Group Publishing, London, pp. 191-208. ISBN 1-930708-25-4. (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:13671)

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.

Abstract

Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no longer capable of handling this level of complexity, heuristic search methods have attracted increasing attention in recent years for solving such problems. Inspired by nature, biology, statistical mechanics, physics and neuroscience, heuristics techniques are used to solve many problems where traditional methods have failed. Data Mining: A Hueristic Approach will be a repository for the applications of these techniques in the area of data mining.

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 Nov 2021 09:51 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/13671 (The current URI for this page, for reference purposes)

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