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 available from this repository)

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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: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 17:59
Last Modified: 08 Apr 2014 09:10
Resource URI: http://kar.kent.ac.uk/id/eprint/13671 (The current URI for this page, for reference purposes)
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