Rule Discovery for Binary Classification Problem using ACO based Antminer

Data mining can be performed by number of ways. Classification is one of them. Classification is a data mining technique that assigns items to a predefined categories or classes or labels. The aim of classification is to predict the target class for the inputted data. On the other hand biology inspired algorithms such as Genetic Algorithms (GA) and Swarm based approaches like Particle Swarm Optimization (PSO) and Ant Colonies Optimization (ACO) were used in solving many data mining problems and currently the most prominent choice in the area of swarm intelligence. In this paper binary classification is considered as an area of problem and a modified AntMiner is used to solve the problem. The basic algorithm of AntMiner has been modified with a different classification accuracy function.