A New Classification-Rule Pruning Procedure for an Ant Colony Algorithm

Chan, Allen and Freitas, Alex A. (2006) A New Classification-Rule Pruning Procedure for an Ant Colony Algorithm. In: Talbi, El-Ghazali and Liardet, Pierre and Collet, Pierre and Lutton, Evelyne and Schoenauer, Marc, eds. Artificial Evolution. Lecture Notes In Computer Science , 3871. Springer pp. 25-36. ISBN 3540335897. (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)

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This work proposes a new rule pruning procedure for Ant-Miner, an Ant Colony algorithm that discovers classification rules in the context of data mining. The performance of Ant-Miner with the new pruning procedure is evaluated and compared with the performance of the original Ant-Miner across several datasets. The results show that the new pruning procedure has a mixed effect on the performance of Ant-Miner. On one hand, overall it tends to decrease the classification accuracy more often than it improves it. On the other hand, the new pruning procedure in general leads to the discovery of classification rules that are considerably shorter, and so simpler (more easily interpretable by the users) than the rules discovered by the original Ant-Miner.

Item Type: Conference or workshop item (UNSPECIFIED)
Uncontrolled keywords: data mining, ant colony optimization, classification
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 18:02
Last Modified: 19 Jun 2014 10:12
Resource URI: https://kar.kent.ac.uk/id/eprint/14244 (The current URI for this page, for reference purposes)
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