Classification Rule Discovery with Ant Colony Optimization

Volume 9, Issue 4, pp 352 - 361 http://dx.doi.org/10.22436/jmcs.09.04.11

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Authors

Kayvan Azaryuon - Department of Computer Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran. Babak Fakhar - Department of Computer Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran. Ali Daghaieghi - Information &Communication Department National Iranian Drilling Company IRAN.

Abstract

This paper proposes an algorithm for data mining called Ant-Miner (ant-colony-based data miner). The goal of Ant-Miner is to extract classification rules from data. The algorithm is inspired by both researches on the behavior of real ant colonies and some data mining concepts as well as principles. Recently research shows that ant colony optimization algorithm have been applied successfully to combinatorial optimization problems. In this paper we present an improvement to Ant-Miner. We compare the performance of new algorithm with before algorithm in two public domain data sets.

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Keywords

• Ant Colony
• Classification Rules
• Data mining
• Extract knowledge
• Database.

MSC

•  68T05

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