Classification Rule Discovery with Ant Colony Optimization

—Ant-based algorithms or ant colony optimization (ACO) algorithms have been applied successfully to combinatorial optimization problems. More recently, Parpinelli and colleagues applied ACO to data mining classification problems, where they introduced a classification algorithm called Ant_Miner. In this paper, we present an improvement to Ant_Miner (we call it Ant_Miner3). The proposed version was tested on two standard problems and performed better than the original Ant_Miner algorithm. The remainder of the paper is organized as follow. In section 1, we present the basic idea of the ant colony systems. In section 2, the Ant_Miner algorithm (Rafael S.Parpinelli et al, 2000) is introduced. In section 3, the density based Ant_miner2 is explained. In section 4, our further improved method (i.e.Ant_Miner3) is shown. Then the computational results are reported in section 5. Finally, we conclude with general remarks on this work and further directions for future research.

• Type: Conference
• Year: 2003
• Where: IAT
• Authors: Bo Liu, Hussein A. Abbass, Bob McKay
• Keywords: Algorithm, Ant Colony, Ant_Miner Algorithm, IAT 2003, Intelligent Agent