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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: Dorigo, Marco, ed. Ant Colony Optimization and Swarm Intelligence 6th International Conference. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 48-59. ISBN 978-3-540-87526-0. E-ISBN 978-3-540-87527-7. (doi:10.1007/978-3-540-87527-7_5) (KAR id:24014)


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: Book section
DOI/Identification number: 10.1007/978-3-540-87527-7_5
Uncontrolled keywords: ant colony optimisation, classification, data mining
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: Fernando Otero
Date Deposited: 29 Mar 2010 12:10 UTC
Last Modified: 16 Nov 2021 10:02 UTC
Resource URI: (The current URI for this page, for reference purposes)

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