Classification Rule Discovery with Ant Colony Optimization
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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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ISRP Style
Kayvan Azaryuon, Babak Fakhar, Ali Daghaieghi, Classification Rule Discovery with Ant Colony Optimization, Journal of Mathematics and Computer Science, 9 (2014), no. 4, 352 - 361
AMA Style
Azaryuon Kayvan, Fakhar Babak, Daghaieghi Ali, Classification Rule Discovery with Ant Colony Optimization. J Math Comput SCI-JM. (2014); 9(4):352 - 361
Chicago/Turabian Style
Azaryuon, Kayvan, Fakhar, Babak, Daghaieghi, Ali. "Classification Rule Discovery with Ant Colony Optimization." Journal of Mathematics and Computer Science, 9, no. 4 (2014): 352 - 361
Keywords
- Ant Colony
- Classification Rules
- Data mining
- Extract knowledge
- Database.
MSC
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