Title of article :
Classification Rule Discovery with Ant Colony Optimization
Author/Authors :
Azaryuon، Kayvan نويسنده Department of Computer Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran , , Fakhar، Babak نويسنده , , Daghaieghi، Ali نويسنده Information &Communication Department National Iranian Drilling Company IRAN ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Pages :
10
From page :
352
To page :
361
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.
Journal title :
The Journal of Mathematics and Computer Science(JMCS)
Serial Year :
2014
Journal title :
The Journal of Mathematics and Computer Science(JMCS)
Record number :
1519092
Link To Document :
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