Learning of Classification Rules Through Ant Colony Optimization Method
Ant Colony Optimization (ACO) algorithm is gaining major interest as a well-known meta heuristic technique. ACO has a prospective application as a data classifier. The use of ant miner may become very effective for learning of classification rules. Nowadays the field of multi objective optimization is dealing with such mission critical aims. Their main objective is to use a multistage ant miner as an efficient classifier. In initial stage the authors will use ant miner for reduction of rule set. In the consequent stage they will use the method of adaptation and transformation for higher rate of convergence. In their experimental studies they have found it to be effective and fairly accurate for classification.