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Using a unified measure function for heuristics, discretization, and rule quality evaluation in Ant-Miner

Salama, Khalid M., Otero, Fernando E.B. (2013) Using a unified measure function for heuristics, discretization, and rule quality evaluation in Ant-Miner. In: IEEE Congress on Evolutionary Computation (CEC). . pp. 900-907. IEEE ISBN 978-1-4799-0453-2. E-ISBN 978-1-4799-0454-9. (doi:10.1109/CEC.2013.6557663) (KAR id:42139)

Abstract

Ant-Miner is a classification rule discovery algorithm that is based on Ant Colony Optimization (ACO) meta-heuristic. cAnt-Miner is the extended version of the algorithm that handles continuous attributes on-the-fly during the rule construction process, while ?Ant-Miner is an extension of the algorithm that selects the rule class prior to its construction, and utilizes multiple pheromone types, one for each permitted rule class. In this paper, we combine these two algorithms to derive a new approach for learning classification rules using ACO. The proposed approach is based on using the measure function for 1) computing the heuristics for rule term selection, 2) a criteria for discretizing continuous attributes, and 3) evaluating the quality of the constructed rule for pheromone update as well. We explore the effect of using different measure functions for on the output model in terms of predictive accuracy and model size. Empirical evaluations found that hypothesis of different functions produce different results are acceptable according to Friedman’s statistical test.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/CEC.2013.6557663
Uncontrolled keywords: prediction algorithms; accuracy; training; predictive models; heuristic algorithms; size measurement; entropy
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Fernando Otero
Date Deposited: 07 Aug 2014 18:57 UTC
Last Modified: 16 Nov 2021 10:16 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/42139 (The current URI for this page, for reference purposes)

University of Kent Author Information

Otero, Fernando E.B..

Creator's ORCID: https://orcid.org/0000-0003-2172-297X
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