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ABC-Miner: an ant-based Bayesian classification algorithm.

Salama, Khalid M. and Freitas, Alex A. (2012) ABC-Miner: an ant-based Bayesian classification algorithm. In: Swarm Intelligence 8th International Conference. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 13-24. ISBN 978-3-642-32649-3. E-ISBN 978-3-642-32650-9. (doi:10.1007/978-3-642-32650-9_2) (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) (KAR id:32165)

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.
Official URL:
http://dx.doi.org/10.1007/978-3-642-32650-9_2

Abstract

Bayesian networks (BNs) are powerful tools for knowledge representation and inference that encode (in)dependencies among random variables. A Bayesian network classifier is a special kind of these networks that aims to compute the posterior probability of each class given an instance of the attributes and predicts the class with the highest posterior probability. Since learning the optimal BN structure from a dataset is NP -hard, heuristic search algorithms need to be applied effectively to build high-quality networks. In this paper, we propose a novel algorithm, called ABC-Miner, for learning the structure of BN classifiers using the Ant Colony Optimization (ACO) meta-heuristic. We describe all the elements necessary to tackle our learning problem using ACO, and experimentally compare the performance of our ant-based Bayesian classification algorithm with other algorithms for learning BN classifiers used in the literature.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-642-32650-9_2
Uncontrolled keywords: data mining, ant colony optimization
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76.E95 Expert Systems (Intelligent Knowledge Based Systems)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Alex Freitas
Date Deposited: 14 Nov 2012 14:17 UTC
Last Modified: 16 Nov 2021 10:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/32165 (The current URI for this page, for reference purposes)

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