cAnt-Miner: an ant colony classification algorithm to cope with continuous attributes

Otero, Fernando E.B. and Freitas, Alex A. and Johnson, Colin G. (2008) cAnt-Miner: an ant colony classification algorithm to cope with continuous attributes. In: Ant Colony Optimization and Swarm Intelligence (Proc. ANTS 2008), LNCS 5217, SEP 22-24, 2008, Brussels, BELGIUM. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1007/978-3-540-87527-7

Abstract

This paper presents an extension to Ant-Miner, named cAnt-Miner (Ant-Miner coping with continuous attributes), which incorporates an entropy-based discretization method in order to cope with continuous attributes during the rule construction process. By having the ability to create discrete intervals for continuous attributes "on-the-fly", cAnt-Miner does not requires a discretization method in a preprocessing step, as Ant-Miner requires. cAnt-Miner has been compared against Ant-Miner in eight public domain datasets with respect to predictive accuracy and simplicity of the discovered rules. Empirical results show that creating discrete intervals during the rule construction process facilitates the discovery of more accurate and significantly simpler classification rules

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: ant colony optimisation, classification, data mining
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: 29 Mar 2010 12:10
Last Modified: 02 Jul 2014 10:37
Resource URI: http://kar.kent.ac.uk/id/eprint/24014 (The current URI for this page, for reference purposes)
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